graphkit-learn/notebooks/.ipynb_checkpoints/run_untildpathkernel_acyclic-checkpoint.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.09047365188598633 seconds ---\n",
      "[[ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
      "   0.33333333]\n",
      " [ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
      "   0.33333333]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " ..., \n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 43.616902\n",
      "With standard deviation: 2.132120\n",
      "\n",
      " Mean performance on test set: 41.620214\n",
      "With standard deviation: 6.453003\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.1754138469696045 seconds ---\n",
      "[[ 1.          0.8         0.14285714 ...,  0.125       0.125       0.125     ]\n",
      " [ 0.8         1.          0.125      ...,  0.11111111  0.11111111\n",
      "   0.11111111]\n",
      " [ 0.14285714  0.125       1.         ...,  0.8         0.8         0.8       ]\n",
      " ..., \n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 40.832861\n",
      "With standard deviation: 3.441465\n",
      "\n",
      " Mean performance on test set: 38.844613\n",
      "With standard deviation: 6.446482\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.3448960781097412 seconds ---\n",
      "[[ 1.          0.5         0.11111111 ...,  0.07692308  0.07692308\n",
      "   0.07692308]\n",
      " [ 0.5         1.          0.09090909 ...,  0.06666667  0.06666667\n",
      "   0.06666667]\n",
      " [ 0.11111111  0.09090909  1.         ...,  0.55555556  0.55555556\n",
      "   0.55555556]\n",
      " ..., \n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 35.746142\n",
      "With standard deviation: 1.611340\n",
      "\n",
      " Mean performance on test set: 35.291451\n",
      "With standard deviation: 4.781298\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.5539388656616211 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.05555556  0.05555556\n",
      "   0.05555556]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.04761905  0.04761905\n",
      "   0.04761905]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.35714286  0.35714286\n",
      "   0.35714286]\n",
      " ..., \n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 28.464581\n",
      "With standard deviation: 3.001371\n",
      "\n",
      " Mean performance on test set: 29.484499\n",
      "With standard deviation: 3.903507\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.7706489562988281 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.04347826  0.04166667\n",
      "   0.04347826]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03846154  0.03703704\n",
      "   0.03846154]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.26315789  0.25        0.26315789]\n",
      " ..., \n",
      " [ 0.04347826  0.03846154  0.26315789 ...,  1.          0.95        0.9       ]\n",
      " [ 0.04166667  0.03703704  0.25       ...,  0.95        1.          0.95      ]\n",
      " [ 0.04347826  0.03846154  0.26315789 ...,  0.9         0.95        1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 19.251747\n",
      "With standard deviation: 3.428930\n",
      "\n",
      " Mean performance on test set: 22.669312\n",
      "With standard deviation: 6.280526\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.015580415725708 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03703704  0.03333333\n",
      "   0.03571429]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03333333  0.03030303\n",
      "   0.03225806]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.2173913   0.19230769\n",
      "   0.20833333]\n",
      " ..., \n",
      " [ 0.03703704  0.03333333  0.2173913  ...,  1.          0.88461538\n",
      "   0.74074074]\n",
      " [ 0.03333333  0.03030303  0.19230769 ...,  0.88461538  1.          0.85185185]\n",
      " [ 0.03571429  0.03225806  0.20833333 ...,  0.74074074  0.85185185  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 16.886016\n",
      "With standard deviation: 2.605194\n",
      "\n",
      " Mean performance on test set: 21.795626\n",
      "With standard deviation: 5.522502\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.3330223560333252 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03333333  0.02857143\n",
      "   0.03030303]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03030303  0.02631579\n",
      "   0.02777778]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.19230769  0.16129032\n",
      "   0.17241379]\n",
      " ..., \n",
      " [ 0.03333333  0.03030303  0.19230769 ...,  1.          0.83870968\n",
      "   0.57142857]\n",
      " [ 0.02857143  0.02631579  0.16129032 ...,  0.83870968  1.          0.71428571]\n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  0.57142857  0.71428571  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 13.109746\n",
      "With standard deviation: 2.584308\n",
      "\n",
      " Mean performance on test set: 20.604920\n",
      "With standard deviation: 5.499831\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.602663278579712 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03125     0.02564103\n",
      "   0.02631579]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02857143  0.02380952\n",
      "   0.02439024]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17857143  0.14285714\n",
      "   0.14705882]\n",
      " ..., \n",
      " [ 0.03125     0.02857143  0.17857143 ...,  1.          0.8         0.47619048]\n",
      " [ 0.02564103  0.02380952  0.14285714 ...,  0.8         1.          0.56818182]\n",
      " [ 0.02631579  0.02439024  0.14705882 ...,  0.47619048  0.56818182  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 12.015210\n",
      "With standard deviation: 2.592798\n",
      "\n",
      " Mean performance on test set: 20.347932\n",
      "With standard deviation: 5.176314\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.8121819496154785 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02325581]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.02173913]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.12820513]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.41666667]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.49019608]\n",
      " [ 0.02325581  0.02173913  0.12820513 ...,  0.41666667  0.49019608  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.798096\n",
      "With standard deviation: 2.130816\n",
      "\n",
      " Mean performance on test set: 19.822797\n",
      "With standard deviation: 5.137687\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.2172586917877197 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.0212766 ]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727  0.02      ]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11627907]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.38461538]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.45454545]\n",
      " [ 0.0212766   0.02        0.11627907 ...,  0.38461538  0.45454545  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.799656\n",
      "With standard deviation: 2.095494\n",
      "\n",
      " Mean performance on test set: 19.873364\n",
      "With standard deviation: 5.103689\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.4100613594055176 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 11.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 11 of size 185 built in 2.7440149784088135 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 12.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 12 of size 185 built in 2.723442316055298 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 13.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 13 of size 185 built in 2.6163382530212402 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 14.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 14 of size 185 built in 2.629500389099121 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 15.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 15 of size 185 built in 2.664158821105957 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 16.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 16 of size 185 built in 2.7301340103149414 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 17.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 17 of size 185 built in 2.6328580379486084 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 18.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- kernel matrix of path kernel up to 18 of size 185 built in 2.592944383621216 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 19.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 19 of size 185 built in 2.6368520259857178 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 20.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 20 of size 185 built in 2.52734375 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.778685\n",
      "With standard deviation: 2.100015\n",
      "\n",
      " Mean performance on test set: 19.870809\n",
      "With standard deviation: 5.092173\n",
      "\n",
      "\n",
      "  depth    rmse_test    std_test    rmse_train    std_train     k_time\n",
      "-------  -----------  ----------  ------------  -----------  ---------\n",
      "      0      41.6202     6.453         43.6169      2.13212  0.0904737\n",
      "      1      38.8446     6.44648       40.8329      3.44147  0.175414\n",
      "      2      35.2915     4.7813        35.7461      1.61134  0.344896\n",
      "      3      29.4845     3.90351       28.4646      3.00137  0.553939\n",
      "      4      22.6693     6.28053       19.2517      3.42893  0.770649\n",
      "      5      21.7956     5.5225        16.886       2.60519  1.01558\n",
      "      6      20.6049     5.49983       13.1097      2.58431  1.33302\n",
      "      7      20.3479     5.17631       12.0152      2.5928   1.60266\n",
      "      8      19.8228     5.13769       10.7981      2.13082  1.81218\n",
      "      9      19.8734     5.10369       10.7997      2.09549  2.21726\n",
      "     10      19.8708     5.09217       10.7787      2.10002  2.41006\n",
      "     11      19.8708     5.09217       10.7787      2.10002  2.74401\n",
      "     12      19.8708     5.09217       10.7787      2.10002  2.72344\n",
      "     13      19.8708     5.09217       10.7787      2.10002  2.61634\n",
      "     14      19.8708     5.09217       10.7787      2.10002  2.6295\n",
      "     15      19.8708     5.09217       10.7787      2.10002  2.66416\n",
      "     16      19.8708     5.09217       10.7787      2.10002  2.73013\n",
      "     17      19.8708     5.09217       10.7787      2.10002  2.63286\n",
      "     18      19.8708     5.09217       10.7787      2.10002  2.59294\n",
      "     19      19.8708     5.09217       10.7787      2.10002  2.63685\n",
      "     20      19.8708     5.09217       10.7787      2.10002  2.52734\n",
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.1027534008026123 seconds ---\n",
      "[[ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
      "   0.33333333]\n",
      " [ 1.          1.          0.33333333 ...,  0.33333333  0.33333333\n",
      "   0.33333333]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " ..., \n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]\n",
      " [ 0.33333333  0.33333333  1.         ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 42.787136\n",
      "With standard deviation: 0.675806\n",
      "\n",
      " Mean performance on test set: 42.645892\n",
      "With standard deviation: 6.560629\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.18301701545715332 seconds ---\n",
      "[[ 1.          0.8         0.14285714 ...,  0.125       0.125       0.125     ]\n",
      " [ 0.8         1.          0.125      ...,  0.11111111  0.11111111\n",
      "   0.11111111]\n",
      " [ 0.14285714  0.125       1.         ...,  0.8         0.8         0.8       ]\n",
      " ..., \n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]\n",
      " [ 0.125       0.11111111  0.8        ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 38.880117\n",
      "With standard deviation: 0.623999\n",
      "\n",
      " Mean performance on test set: 39.174317\n",
      "With standard deviation: 6.195371\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.33235955238342285 seconds ---\n",
      "[[ 1.          0.5         0.11111111 ...,  0.07692308  0.07692308\n",
      "   0.07692308]\n",
      " [ 0.5         1.          0.09090909 ...,  0.06666667  0.06666667\n",
      "   0.06666667]\n",
      " [ 0.11111111  0.09090909  1.         ...,  0.55555556  0.55555556\n",
      "   0.55555556]\n",
      " ..., \n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]\n",
      " [ 0.07692308  0.06666667  0.55555556 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 35.348332\n",
      "With standard deviation: 0.727833\n",
      "\n",
      " Mean performance on test set: 35.604226\n",
      "With standard deviation: 4.539211\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.5400393009185791 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.05555556  0.05555556\n",
      "   0.05555556]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.04761905  0.04761905\n",
      "   0.04761905]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.35714286  0.35714286\n",
      "   0.35714286]\n",
      " ..., \n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.04761905  0.35714286 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 28.047646\n",
      "With standard deviation: 1.077805\n",
      "\n",
      " Mean performance on test set: 30.192177\n",
      "With standard deviation: 5.110324\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8054666519165039 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.04347826  0.04166667\n",
      "   0.04347826]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03846154  0.03703704\n",
      "   0.03846154]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.26315789  0.25        0.26315789]\n",
      " ..., \n",
      " [ 0.04347826  0.03846154  0.26315789 ...,  1.          0.95        0.9       ]\n",
      " [ 0.04166667  0.03703704  0.25       ...,  0.95        1.          0.95      ]\n",
      " [ 0.04347826  0.03846154  0.26315789 ...,  0.9         0.95        1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Mean performance on train set: 18.878595\n",
      "With standard deviation: 1.711897\n",
      "\n",
      " Mean performance on test set: 23.751530\n",
      "With standard deviation: 7.808559\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.0195980072021484 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03703704  0.03333333\n",
      "   0.03571429]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03333333  0.03030303\n",
      "   0.03225806]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.2173913   0.19230769\n",
      "   0.20833333]\n",
      " ..., \n",
      " [ 0.03703704  0.03333333  0.2173913  ...,  1.          0.88461538\n",
      "   0.74074074]\n",
      " [ 0.03333333  0.03030303  0.19230769 ...,  0.88461538  1.          0.85185185]\n",
      " [ 0.03571429  0.03225806  0.20833333 ...,  0.74074074  0.85185185  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 16.339135\n",
      "With standard deviation: 1.397693\n",
      "\n",
      " Mean performance on test set: 23.482309\n",
      "With standard deviation: 7.727117\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.2962956428527832 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03333333  0.02857143\n",
      "   0.03030303]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.03030303  0.02631579\n",
      "   0.02777778]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.19230769  0.16129032\n",
      "   0.17241379]\n",
      " ..., \n",
      " [ 0.03333333  0.03030303  0.19230769 ...,  1.          0.83870968\n",
      "   0.57142857]\n",
      " [ 0.02857143  0.02631579  0.16129032 ...,  0.83870968  1.          0.71428571]\n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  0.57142857  0.71428571  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 12.523830\n",
      "With standard deviation: 1.040404\n",
      "\n",
      " Mean performance on test set: 22.745367\n",
      "With standard deviation: 8.028051\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.5462064743041992 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03125     0.02564103\n",
      "   0.02631579]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02857143  0.02380952\n",
      "   0.02439024]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17857143  0.14285714\n",
      "   0.14705882]\n",
      " ..., \n",
      " [ 0.03125     0.02857143  0.17857143 ...,  1.          0.8         0.47619048]\n",
      " [ 0.02564103  0.02380952  0.14285714 ...,  0.8         1.          0.56818182]\n",
      " [ 0.02631579  0.02439024  0.14705882 ...,  0.47619048  0.56818182  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 11.371668\n",
      "With standard deviation: 0.925446\n",
      "\n",
      " Mean performance on test set: 22.831602\n",
      "With standard deviation: 7.978369\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.8658208847045898 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02325581]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.02173913]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.12820513]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.41666667]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.49019608]\n",
      " [ 0.02325581  0.02173913  0.12820513 ...,  0.41666667  0.49019608  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.132106\n",
      "With standard deviation: 0.525580\n",
      "\n",
      " Mean performance on test set: 22.586071\n",
      "With standard deviation: 8.067887\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.185042381286621 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.0212766 ]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727  0.02      ]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11627907]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.38461538]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.45454545]\n",
      " [ 0.0212766   0.02        0.11627907 ...,  0.38461538  0.45454545  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.078464\n",
      "With standard deviation: 0.518149\n",
      "\n",
      " Mean performance on test set: 22.766801\n",
      "With standard deviation: 8.005709\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.35276198387146 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 11.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 11 of size 185 built in 2.6274359226226807 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 12.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 12 of size 185 built in 2.7209105491638184 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 13.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 13 of size 185 built in 2.699059247970581 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 14.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 14 of size 185 built in 2.6328344345092773 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 15.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 15 of size 185 built in 2.6556999683380127 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 16.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 16 of size 185 built in 2.621814012527466 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 17.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 17 of size 185 built in 2.5938243865966797 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 18.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 18 of size 185 built in 2.65336275100708 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 19.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 19 of size 185 built in 2.628486156463623 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 20.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 20 of size 185 built in 2.682689666748047 seconds ---\n",
      "[[ 1.          0.44444444  0.11111111 ...,  0.03030303  0.02439024\n",
      "   0.02040816]\n",
      " [ 0.44444444  1.          0.08333333 ...,  0.02777778  0.02272727\n",
      "   0.01923077]\n",
      " [ 0.11111111  0.08333333  1.         ...,  0.17241379  0.13513514\n",
      "   0.11111111]\n",
      " ..., \n",
      " [ 0.03030303  0.02777778  0.17241379 ...,  1.          0.73684211\n",
      "   0.37037037]\n",
      " [ 0.02439024  0.02272727  0.13513514 ...,  0.73684211  1.          0.43859649]\n",
      " [ 0.02040816  0.01923077  0.11111111 ...,  0.37037037  0.43859649  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.075607\n",
      "With standard deviation: 0.672820\n",
      "\n",
      " Mean performance on test set: 22.869720\n",
      "With standard deviation: 7.944560\n",
      "\n",
      "\n",
      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
      "-------  -----------  ----------  ------------  -----------  --------\n",
      "      0      42.6459     6.56063       42.7871     0.675806  0.102753\n",
      "      1      39.1743     6.19537       38.8801     0.623999  0.183017\n",
      "      2      35.6042     4.53921       35.3483     0.727833  0.33236\n",
      "      3      30.1922     5.11032       28.0476     1.0778    0.540039\n",
      "      4      23.7515     7.80856       18.8786     1.7119    0.805467\n",
      "      5      23.4823     7.72712       16.3391     1.39769   1.0196\n",
      "      6      22.7454     8.02805       12.5238     1.0404    1.2963\n",
      "      7      22.8316     7.97837       11.3717     0.925446  1.54621\n",
      "      8      22.5861     8.06789       10.1321     0.52558   1.86582\n",
      "      9      22.7668     8.00571       10.0785     0.518149  2.18504\n",
      "     10      22.8697     7.94456       10.0756     0.67282   2.35276\n",
      "     11      22.8697     7.94456       10.0756     0.67282   2.62744\n",
      "     12      22.8697     7.94456       10.0756     0.67282   2.72091\n",
      "     13      22.8697     7.94456       10.0756     0.67282   2.69906\n",
      "     14      22.8697     7.94456       10.0756     0.67282   2.63283\n",
      "     15      22.8697     7.94456       10.0756     0.67282   2.6557\n",
      "     16      22.8697     7.94456       10.0756     0.67282   2.62181\n",
      "     17      22.8697     7.94456       10.0756     0.67282   2.59382\n",
      "     18      22.8697     7.94456       10.0756     0.67282   2.65336\n",
      "     19      22.8697     7.94456       10.0756     0.67282   2.62849\n",
      "     20      22.8697     7.94456       10.0756     0.67282   2.68269\n",
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.3893899917602539 seconds ---\n",
      "[[ 1.          0.75        0.5        ...,  0.16666667  0.16666667\n",
      "   0.16666667]\n",
      " [ 0.75        1.          0.4        ...,  0.15384615  0.15384615\n",
      "   0.15384615]\n",
      " [ 0.5         0.4         1.         ...,  0.27272727  0.27272727\n",
      "   0.27272727]\n",
      " ..., \n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 12.207923\n",
      "With standard deviation: 0.700182\n",
      "\n",
      " Mean performance on test set: 12.682718\n",
      "With standard deviation: 2.748815\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.4729621410369873 seconds ---\n",
      "[[ 1.          0.7         0.16666667 ...,  0.05555556  0.05555556\n",
      "   0.05555556]\n",
      " [ 0.7         1.          0.13333333 ...,  0.05128205  0.05128205\n",
      "   0.05128205]\n",
      " [ 0.16666667  0.13333333  1.         ...,  0.22580645  0.22580645\n",
      "   0.22580645]\n",
      " ..., \n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.279220\n",
      "With standard deviation: 0.914688\n",
      "\n",
      " Mean performance on test set: 12.609828\n",
      "With standard deviation: 2.372778\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.576836109161377 seconds ---\n",
      "[[ 1.          0.4375      0.125      ...,  0.03333333  0.03333333\n",
      "   0.03571429]\n",
      " [ 0.4375      1.          0.0952381  ...,  0.03076923  0.03076923\n",
      "   0.03278689]\n",
      " [ 0.125       0.0952381   1.         ...,  0.16981132  0.16981132\n",
      "   0.18367347]\n",
      " ..., \n",
      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
      " [ 0.03571429  0.03278689  0.18367347 ...,  0.9245283   0.9245283   1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 2.588811\n",
      "With standard deviation: 0.557162\n",
      "\n",
      " Mean performance on test set: 8.060609\n",
      "With standard deviation: 2.470450\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.7169125080108643 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.02631579  0.02631579\n",
      "   0.02777778]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.02409639  0.02409639\n",
      "   0.02531646]\n",
      " [ 0.125       0.08695652  1.         ...,  0.13043478  0.13043478\n",
      "   0.13846154]\n",
      " ..., \n",
      " [ 0.02631579  0.02409639  0.13043478 ...,  1.          0.94366197\n",
      "   0.83561644]\n",
      " [ 0.02631579  0.02409639  0.13043478 ...,  0.94366197  1.          0.78666667]\n",
      " [ 0.02777778  0.02531646  0.13846154 ...,  0.83561644  0.78666667  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.272670\n",
      "With standard deviation: 0.760432\n",
      "\n",
      " Mean performance on test set: 9.755135\n",
      "With standard deviation: 3.049170\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8342421054840088 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.02222222  0.02222222\n",
      "   0.02325581]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.02061856  0.02061856\n",
      "   0.02150538]\n",
      " [ 0.125       0.08695652  1.         ...,  0.10843373  0.10843373\n",
      "   0.11392405]\n",
      " ..., \n",
      " [ 0.02222222  0.02061856  0.10843373 ...,  1.          0.82417582\n",
      "   0.67010309]\n",
      " [ 0.02222222  0.02061856  0.10843373 ...,  0.82417582  1.          0.70526316]\n",
      " [ 0.02325581  0.02150538  0.11392405 ...,  0.67010309  0.70526316  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.032293\n",
      "With standard deviation: 0.728380\n",
      "\n",
      " Mean performance on test set: 10.319167\n",
      "With standard deviation: 3.616673\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 5 of size 185 built in 0.9938209056854248 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01960784  0.01960784\n",
      "   0.02040816]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01834862  0.01834862\n",
      "   0.01904762]\n",
      " [ 0.125       0.08695652  1.         ...,  0.09473684  0.09473684\n",
      "   0.0989011 ]\n",
      " ..., \n",
      " [ 0.01960784  0.01834862  0.09473684 ...,  1.          0.74311927\n",
      "   0.56302521]\n",
      " [ 0.01960784  0.01834862  0.09473684 ...,  0.74311927  1.          0.6173913 ]\n",
      " [ 0.02040816  0.01904762  0.0989011  ...,  0.56302521  0.6173913   1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 0.923543\n",
      "With standard deviation: 0.660532\n",
      "\n",
      " Mean performance on test set: 10.659250\n",
      "With standard deviation: 4.120523\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.1753439903259277 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01785714  0.01785714\n",
      "   0.01851852]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01680672  0.01680672\n",
      "   0.0173913 ]\n",
      " [ 0.125       0.08695652  1.         ...,  0.08571429  0.08571429\n",
      "   0.08910891]\n",
      " ..., \n",
      " [ 0.01785714  0.01680672  0.08571429 ...,  1.          0.68        0.48201439]\n",
      " [ 0.01785714  0.01680672  0.08571429 ...,  0.68        1.          0.54887218]\n",
      " [ 0.01851852  0.0173913   0.08910891 ...,  0.48201439  0.54887218  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 0.878589\n",
      "With standard deviation: 0.603598\n",
      "\n",
      " Mean performance on test set: 11.102521\n",
      "With standard deviation: 4.330554\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.4358420372009277 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01666667  0.01666667\n",
      "   0.01724138]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01574803  0.01574803\n",
      "   0.01626016]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07964602  0.07964602\n",
      "   0.08256881]\n",
      " ..., \n",
      " [ 0.01666667  0.01574803  0.07964602 ...,  1.          0.64963504\n",
      "   0.43225806]\n",
      " [ 0.01666667  0.01574803  0.07964602 ...,  0.64963504  1.          0.48993289]\n",
      " [ 0.01724138  0.01626016  0.08256881 ...,  0.43225806  0.48993289  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 0.944049\n",
      "With standard deviation: 0.694844\n",
      "\n",
      " Mean performance on test set: 11.352962\n",
      "With standard deviation: 4.305459\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.7005987167358398 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
      "   0.01639344]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01550388]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07826087]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.3964497 ]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.44785276]\n",
      " [ 0.01639344  0.01550388  0.07826087 ...,  0.3964497   0.44785276  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.033979\n",
      "With standard deviation: 0.775622\n",
      "\n",
      " Mean performance on test set: 11.298981\n",
      "With standard deviation: 4.349648\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- kernel matrix of path kernel up to 9 of size 185 built in 2.0194287300109863 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
      "   0.01587302]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01503759]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07563025]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.38728324]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43712575]\n",
      " [ 0.01587302  0.01503759  0.07563025 ...,  0.38728324  0.43712575  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.003187\n",
      "With standard deviation: 0.572070\n",
      "\n",
      " Mean performance on test set: 11.332669\n",
      "With standard deviation: 4.324120\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.243326187133789 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625    0.015625  ]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01481481]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07438017]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.38285714]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43195266]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.38285714  0.43195266  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.002272\n",
      "With standard deviation: 0.570937\n",
      "\n",
      " Mean performance on test set: 11.343515\n",
      "With standard deviation: 4.327265\n",
      "\n",
      "\n",
      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
      "-------  -----------  ----------  ------------  -----------  --------\n",
      "      0     12.6827      2.74882     12.2079       0.700182  0.38939\n",
      "      1     12.6098      2.37278     10.2792       0.914688  0.472962\n",
      "      2      8.06061     2.47045      2.58881      0.557162  0.576836\n",
      "      3      9.75514     3.04917      1.27267      0.760432  0.716913\n",
      "      4     10.3192      3.61667      1.03229      0.72838   0.834242\n",
      "      5     10.6593      4.12052      0.923543     0.660532  0.993821\n",
      "      6     11.1025      4.33055      0.878589     0.603598  1.17534\n",
      "      7     11.353       4.30546      0.944049     0.694844  1.43584\n",
      "      8     11.299       4.34965      1.03398      0.775622  1.7006\n",
      "      9     11.3327      4.32412      1.00319      0.57207   2.01943\n",
      "     10     11.3435      4.32726      1.00227      0.570937  2.24333\n",
      "\n",
      " --- This is a regression problem ---\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 0.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 0 of size 185 built in 0.3775763511657715 seconds ---\n",
      "[[ 1.          0.75        0.5        ...,  0.16666667  0.16666667\n",
      "   0.16666667]\n",
      " [ 0.75        1.          0.4        ...,  0.15384615  0.15384615\n",
      "   0.15384615]\n",
      " [ 0.5         0.4         1.         ...,  0.27272727  0.27272727\n",
      "   0.27272727]\n",
      " ..., \n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]\n",
      " [ 0.16666667  0.15384615  0.27272727 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 12.120872\n",
      "With standard deviation: 0.500467\n",
      "\n",
      " Mean performance on test set: 12.579966\n",
      "With standard deviation: 2.732346\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 1.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 1 of size 185 built in 0.4563324451446533 seconds ---\n",
      "[[ 1.          0.7         0.16666667 ...,  0.05555556  0.05555556\n",
      "   0.05555556]\n",
      " [ 0.7         1.          0.13333333 ...,  0.05128205  0.05128205\n",
      "   0.05128205]\n",
      " [ 0.16666667  0.13333333  1.         ...,  0.22580645  0.22580645\n",
      "   0.22580645]\n",
      " ..., \n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]\n",
      " [ 0.05555556  0.05128205  0.22580645 ...,  1.          1.          1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 10.224322\n",
      "With standard deviation: 0.734261\n",
      "\n",
      " Mean performance on test set: 12.621509\n",
      "With standard deviation: 2.188664\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 2.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 2 of size 185 built in 0.5852782726287842 seconds ---\n",
      "[[ 1.          0.4375      0.125      ...,  0.03333333  0.03333333\n",
      "   0.03571429]\n",
      " [ 0.4375      1.          0.0952381  ...,  0.03076923  0.03076923\n",
      "   0.03278689]\n",
      " [ 0.125       0.0952381   1.         ...,  0.16981132  0.16981132\n",
      "   0.18367347]\n",
      " ..., \n",
      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
      " [ 0.03333333  0.03076923  0.16981132 ...,  1.          1.          0.9245283 ]\n",
      " [ 0.03571429  0.03278689  0.18367347 ...,  0.9245283   0.9245283   1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 2.718851\n",
      "With standard deviation: 0.732922\n",
      "\n",
      " Mean performance on test set: 7.429032\n",
      "With standard deviation: 2.693953\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 3.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 3 of size 185 built in 0.7065560817718506 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.02631579  0.02631579\n",
      "   0.02777778]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.02409639  0.02409639\n",
      "   0.02531646]\n",
      " [ 0.125       0.08695652  1.         ...,  0.13043478  0.13043478\n",
      "   0.13846154]\n",
      " ..., \n",
      " [ 0.02631579  0.02409639  0.13043478 ...,  1.          0.94366197\n",
      "   0.83561644]\n",
      " [ 0.02631579  0.02409639  0.13043478 ...,  0.94366197  1.          0.78666667]\n",
      " [ 0.02777778  0.02531646  0.13846154 ...,  0.83561644  0.78666667  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.540000\n",
      "With standard deviation: 1.138134\n",
      "\n",
      " Mean performance on test set: 9.024680\n",
      "With standard deviation: 2.508084\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 4.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 4 of size 185 built in 0.8479568958282471 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.02222222  0.02222222\n",
      "   0.02325581]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.02061856  0.02061856\n",
      "   0.02150538]\n",
      " [ 0.125       0.08695652  1.         ...,  0.10843373  0.10843373\n",
      "   0.11392405]\n",
      " ..., \n",
      " [ 0.02222222  0.02061856  0.10843373 ...,  1.          0.82417582\n",
      "   0.67010309]\n",
      " [ 0.02222222  0.02061856  0.10843373 ...,  0.82417582  1.          0.70526316]\n",
      " [ 0.02325581  0.02150538  0.11392405 ...,  0.67010309  0.70526316  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.360291\n",
      "With standard deviation: 1.423990\n",
      "\n",
      " Mean performance on test set: 10.081112\n",
      "With standard deviation: 3.647700\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 5.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 5 of size 185 built in 1.0008597373962402 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01960784  0.01960784\n",
      "   0.02040816]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01834862  0.01834862\n",
      "   0.01904762]\n",
      " [ 0.125       0.08695652  1.         ...,  0.09473684  0.09473684\n",
      "   0.0989011 ]\n",
      " ..., \n",
      " [ 0.01960784  0.01834862  0.09473684 ...,  1.          0.74311927\n",
      "   0.56302521]\n",
      " [ 0.01960784  0.01834862  0.09473684 ...,  0.74311927  1.          0.6173913 ]\n",
      " [ 0.02040816  0.01904762  0.0989011  ...,  0.56302521  0.6173913   1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.085175\n",
      "With standard deviation: 1.062063\n",
      "\n",
      " Mean performance on test set: 11.300476\n",
      "With standard deviation: 4.441634\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 6.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " --- kernel matrix of path kernel up to 6 of size 185 built in 1.1979196071624756 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01785714  0.01785714\n",
      "   0.01851852]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01680672  0.01680672\n",
      "   0.0173913 ]\n",
      " [ 0.125       0.08695652  1.         ...,  0.08571429  0.08571429\n",
      "   0.08910891]\n",
      " ..., \n",
      " [ 0.01785714  0.01680672  0.08571429 ...,  1.          0.68        0.48201439]\n",
      " [ 0.01785714  0.01680672  0.08571429 ...,  0.68        1.          0.54887218]\n",
      " [ 0.01851852  0.0173913   0.08910891 ...,  0.48201439  0.54887218  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.064431\n",
      "With standard deviation: 1.001911\n",
      "\n",
      " Mean performance on test set: 12.186014\n",
      "With standard deviation: 4.888158\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 7.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 7 of size 185 built in 1.4372029304504395 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.01666667  0.01666667\n",
      "   0.01724138]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01574803  0.01574803\n",
      "   0.01626016]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07964602  0.07964602\n",
      "   0.08256881]\n",
      " ..., \n",
      " [ 0.01666667  0.01574803  0.07964602 ...,  1.          0.64963504\n",
      "   0.43225806]\n",
      " [ 0.01666667  0.01574803  0.07964602 ...,  0.64963504  1.          0.48993289]\n",
      " [ 0.01724138  0.01626016  0.08256881 ...,  0.43225806  0.48993289  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.199119\n",
      "With standard deviation: 1.340313\n",
      "\n",
      " Mean performance on test set: 12.753387\n",
      "With standard deviation: 5.145288\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 8.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 8 of size 185 built in 1.68448805809021 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
      "   0.01639344]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01550388]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07826087]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.3964497 ]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.44785276]\n",
      " [ 0.01639344  0.01550388  0.07826087 ...,  0.3964497   0.44785276  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.358221\n",
      "With standard deviation: 1.843147\n",
      "\n",
      " Mean performance on test set: 13.047098\n",
      "With standard deviation: 5.271835\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 9.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 9 of size 185 built in 1.9654510021209717 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625\n",
      "   0.01587302]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01503759]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07563025]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.38728324]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43712575]\n",
      " [ 0.01587302  0.01503759  0.07563025 ...,  0.38728324  0.43712575  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.360024\n",
      "With standard deviation: 1.848342\n",
      "\n",
      " Mean performance on test set: 13.178933\n",
      "With standard deviation: 5.277067\n",
      "\n",
      "\n",
      " #--- calculating kernel matrix when depth = 10.0 ---#\n",
      "\n",
      " Loading dataset from file...\n",
      "\n",
      " Calculating kernel matrix, this could take a while...\n",
      "\n",
      " --- kernel matrix of path kernel up to 10 of size 185 built in 2.2494258880615234 seconds ---\n",
      "[[ 1.          0.38888889  0.125      ...,  0.015625    0.015625    0.015625  ]\n",
      " [ 0.38888889  1.          0.08695652 ...,  0.01481481  0.01481481\n",
      "   0.01481481]\n",
      " [ 0.125       0.08695652  1.         ...,  0.07438017  0.07438017\n",
      "   0.07438017]\n",
      " ..., \n",
      " [ 0.015625    0.01481481  0.07438017 ...,  1.          0.58169935\n",
      "   0.38285714]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.58169935  1.          0.43195266]\n",
      " [ 0.015625    0.01481481  0.07438017 ...,  0.38285714  0.43195266  1.        ]]\n",
      "\n",
      " Saving kernel matrix to file...\n",
      "\n",
      " Mean performance on train set: 1.362078\n",
      "With standard deviation: 1.854262\n",
      "\n",
      " Mean performance on test set: 13.253773\n",
      "With standard deviation: 5.264247\n",
      "\n",
      "\n",
      "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
      "-------  -----------  ----------  ------------  -----------  --------\n",
      "      0     12.58        2.73235      12.1209      0.500467  0.377576\n",
      "      1     12.6215      2.18866      10.2243      0.734261  0.456332\n",
      "      2      7.42903     2.69395       2.71885     0.732922  0.585278\n",
      "      3      9.02468     2.50808       1.54        1.13813   0.706556\n",
      "      4     10.0811      3.6477        1.36029     1.42399   0.847957\n",
      "      5     11.3005      4.44163       1.08518     1.06206   1.00086\n",
      "      6     12.186       4.88816       1.06443     1.00191   1.19792\n",
      "      7     12.7534      5.14529       1.19912     1.34031   1.4372\n",
      "      8     13.0471      5.27184       1.35822     1.84315   1.68449\n",
      "      9     13.1789      5.27707       1.36002     1.84834   1.96545\n",
      "     10     13.2538      5.26425       1.36208     1.85426   2.24943\n"
     ]
    }
   ],
   "source": [
    "%load_ext line_profiler\n",
    "\n",
    "import sys\n",
    "sys.path.insert(0, \"../\")\n",
    "from pygraph.utils.utils import kernel_train_test\n",
    "from pygraph.kernels.untildPathKernel import untildpathkernel\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "datafile = '../../../../datasets/acyclic/Acyclic/dataset_bps.ds'\n",
    "kernel_file_path = 'kernelmatrices_path_acyclic/'\n",
    "\n",
    "kernel_para = dict(node_label = 'atom', edge_label = 'bond_type', labeled = True, k_func = 'tanimoto')\n",
    "\n",
    "# kernel_train_test(datafile, kernel_file_path, treeletkernel, kernel_para, normalize = False)\n",
    "\n",
    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
    "    hyper_name = 'depth', hyper_range = np.linspace(0, 20, 21), normalize = True)\n",
    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
    "    hyper_name = 'depth', hyper_range = np.linspace(0, 20, 21), normalize = False)\n",
    "\n",
    "kernel_para['k_func'] = 'minmax'\n",
    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
    "    hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = True)\n",
    "kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, \\\n",
    "    hyper_name = 'depth', hyper_range = np.linspace(0, 10, 11), normalize = False)\n",
    "\n",
    "# # kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)\n",
    "\n",
    "# kernel_para['depth'] = 10\n",
    "# %lprun -f untildpathkernel \\\n",
    "#     kernel_train_test(datafile, kernel_file_path, untildpathkernel, kernel_para, normalize = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# results\n",
    "\n",
    "# kernel Tanimoto with y normalization\n",
    "  depth    rmse_test    std_test    rmse_train    std_train     k_time\n",
    "-------  -----------  ----------  ------------  -----------  ---------\n",
    "      0      41.6202     6.453         43.6169      2.13212  0.0904737\n",
    "      1      38.8446     6.44648       40.8329      3.44147  0.175414\n",
    "      2      35.2915     4.7813        35.7461      1.61134  0.344896\n",
    "      3      29.4845     3.90351       28.4646      3.00137  0.553939\n",
    "      4      22.6693     6.28053       19.2517      3.42893  0.770649\n",
    "      5      21.7956     5.5225        16.886       2.60519  1.01558\n",
    "      6      20.6049     5.49983       13.1097      2.58431  1.33302\n",
    "      7      20.3479     5.17631       12.0152      2.5928   1.60266\n",
    "      8      19.8228     5.13769       10.7981      2.13082  1.81218\n",
    "      9      19.8734     5.10369       10.7997      2.09549  2.21726\n",
    "     10      19.8708     5.09217       10.7787      2.10002  2.41006\n",
    "     11      19.8708     5.09217       10.7787      2.10002  2.74401\n",
    "     12      19.8708     5.09217       10.7787      2.10002  2.72344\n",
    "     13      19.8708     5.09217       10.7787      2.10002  2.61634\n",
    "     14      19.8708     5.09217       10.7787      2.10002  2.6295\n",
    "     15      19.8708     5.09217       10.7787      2.10002  2.66416\n",
    "     16      19.8708     5.09217       10.7787      2.10002  2.73013\n",
    "     17      19.8708     5.09217       10.7787      2.10002  2.63286\n",
    "     18      19.8708     5.09217       10.7787      2.10002  2.59294\n",
    "     19      19.8708     5.09217       10.7787      2.10002  2.63685\n",
    "     20      19.8708     5.09217       10.7787      2.10002  2.52734\n",
    "\n",
    "# kernel Tanimoto without y normalization\n",
    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
    "-------  -----------  ----------  ------------  -----------  --------\n",
    "      0      42.6459     6.56063       42.7871     0.675806  0.102753\n",
    "      1      39.1743     6.19537       38.8801     0.623999  0.183017\n",
    "      2      35.6042     4.53921       35.3483     0.727833  0.33236\n",
    "      3      30.1922     5.11032       28.0476     1.0778    0.540039\n",
    "      4      23.7515     7.80856       18.8786     1.7119    0.805467\n",
    "      5      23.4823     7.72712       16.3391     1.39769   1.0196\n",
    "      6      22.7454     8.02805       12.5238     1.0404    1.2963\n",
    "      7      22.8316     7.97837       11.3717     0.925446  1.54621\n",
    "      8      22.5861     8.06789       10.1321     0.52558   1.86582\n",
    "      9      22.7668     8.00571       10.0785     0.518149  2.18504\n",
    "     10      22.8697     7.94456       10.0756     0.67282   2.35276\n",
    "     11      22.8697     7.94456       10.0756     0.67282   2.62744\n",
    "     12      22.8697     7.94456       10.0756     0.67282   2.72091\n",
    "     13      22.8697     7.94456       10.0756     0.67282   2.69906\n",
    "     14      22.8697     7.94456       10.0756     0.67282   2.63283\n",
    "     15      22.8697     7.94456       10.0756     0.67282   2.6557\n",
    "     16      22.8697     7.94456       10.0756     0.67282   2.62181\n",
    "     17      22.8697     7.94456       10.0756     0.67282   2.59382\n",
    "     18      22.8697     7.94456       10.0756     0.67282   2.65336\n",
    "     19      22.8697     7.94456       10.0756     0.67282   2.62849\n",
    "     20      22.8697     7.94456       10.0756     0.67282   2.68269\n",
    "    \n",
    "# kernel MinMax with y normalization    \n",
    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
    "-------  -----------  ----------  ------------  -----------  --------\n",
    "      0     12.6827      2.74882     12.2079       0.700182  0.38939\n",
    "      1     12.6098      2.37278     10.2792       0.914688  0.472962\n",
    "      2      8.06061     2.47045      2.58881      0.557162  0.576836\n",
    "      3      9.75514     3.04917      1.27267      0.760432  0.716913\n",
    "      4     10.3192      3.61667      1.03229      0.72838   0.834242\n",
    "      5     10.6593      4.12052      0.923543     0.660532  0.993821\n",
    "      6     11.1025      4.33055      0.878589     0.603598  1.17534\n",
    "      7     11.353       4.30546      0.944049     0.694844  1.43584\n",
    "      8     11.299       4.34965      1.03398      0.775622  1.7006\n",
    "      9     11.3327      4.32412      1.00319      0.57207   2.01943\n",
    "     10     11.3435      4.32726      1.00227      0.570937  2.24333\n",
    "\n",
    "# kernel MinMax without y normalization\n",
    "  depth    rmse_test    std_test    rmse_train    std_train    k_time\n",
    "-------  -----------  ----------  ------------  -----------  --------\n",
    "      0     12.58        2.73235      12.1209      0.500467  0.377576\n",
    "      1     12.6215      2.18866      10.2243      0.734261  0.456332\n",
    "      2      7.42903     2.69395       2.71885     0.732922  0.585278\n",
    "      3      9.02468     2.50808       1.54        1.13813   0.706556\n",
    "      4     10.0811      3.6477        1.36029     1.42399   0.847957\n",
    "      5     11.3005      4.44163       1.08518     1.06206   1.00086\n",
    "      6     12.186       4.88816       1.06443     1.00191   1.19792\n",
    "      7     12.7534      5.14529       1.19912     1.34031   1.4372\n",
    "      8     13.0471      5.27184       1.35822     1.84315   1.68449\n",
    "      9     13.1789      5.27707       1.36002     1.84834   1.96545\n",
    "     10     13.2538      5.26425       1.36208     1.85426   2.24943"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}