From 687e82b882e6a3bd4a95f721d3ef4f42925c07c3 Mon Sep 17 00:00:00 2001 From: linlin Date: Mon, 5 Oct 2020 16:38:27 +0200 Subject: [PATCH] New translations model_selection_old.py (French) --- .../examples/kernels/model_selection_old.py | 38 ++++++++++++++++++++++ 1 file changed, 38 insertions(+) create mode 100644 lang/fr/gklearn/examples/kernels/model_selection_old.py diff --git a/lang/fr/gklearn/examples/kernels/model_selection_old.py b/lang/fr/gklearn/examples/kernels/model_selection_old.py new file mode 100644 index 0000000..ca66be6 --- /dev/null +++ b/lang/fr/gklearn/examples/kernels/model_selection_old.py @@ -0,0 +1,38 @@ +# -*- coding: utf-8 -*- +"""model_selection_old.ipynb + +Automatically generated by Colaboratory. + +Original file is located at + https://colab.research.google.com/drive/1uVkl7scNgEPrimX8ks6iEC5ijuhB8L_D + +**This script demonstrates how to compute a graph kernel.** +--- + +**0. Install `graphkit-learn`.** +""" + +"""**1. Perform model seletion and classification.**""" + +from gklearn.utils import model_selection_for_precomputed_kernel +from gklearn.kernels import untilhpathkernel +import numpy as np + +# Set parameters. +datafile = '../../../datasets/MUTAG/MUTAG_A.txt' +param_grid_precomputed = {'depth': np.linspace(1, 10, 10), + 'k_func': ['MinMax', 'tanimoto'], + 'compute_method': ['trie']} +param_grid = {'C': np.logspace(-10, 10, num=41, base=10)} + +# Perform model selection and classification. +model_selection_for_precomputed_kernel( + datafile, # The path of dataset file. + untilhpathkernel, # The graph kernel used for estimation. + param_grid_precomputed, # The parameters used to compute gram matrices. + param_grid, # The penelty Parameters used for penelty items. + 'classification', # Or 'regression'. + NUM_TRIALS=30, # The number of the random trials of the outer CV loop. + ds_name='MUTAG', # The name of the dataset. + n_jobs=1, + verbose=True) \ No newline at end of file