From 5f8bc3d8a30f6cb2a61b39bb57a6fa38f104d379 Mon Sep 17 00:00:00 2001 From: bushuhui Date: Wed, 30 Sep 2020 08:36:30 +0800 Subject: [PATCH] Add python tutorial and knn sample code --- 0_python/README.md | 7 +- 2_knn/knn_classification.ipynb | 149 ++++++++++++++++++++++++++++++++++++----- 2 files changed, 135 insertions(+), 21 deletions(-) diff --git a/0_python/README.md b/0_python/README.md index 78e3308..dfcf0ab 100644 --- a/0_python/README.md +++ b/0_python/README.md @@ -1,9 +1,9 @@ # 简明Python教程 (90分钟学会Python) -Python 是一门上手简单、功能强大、通用型的脚本编程语言。Python 类库极其丰富,这使得 Python 几乎无所不能,网站开发、软件开发、大数据分析、网络爬虫、机器学习等都不在话下。Python最主要的优点是使用人类的思考方式来编写程序,大多数情况下使用封装好的库能够快速完成给定的任务,虽然执行的效率不一定很高,但是极大的缩短了程序设计、编写、调试的时间,因此非常适合快速尝试、试错。 +Python 是一门上手简单、功能强大、通用型的脚本编程语言。Python 类库极其丰富,这使得 Python 几乎无所不能,网站开发、软件开发、大数据分析、网络爬虫、机器学习等都不在话下。Python最主要的优点是使用人类的思考方式来编写程序,大多数情况下使用封装好的库能够快速完成给定的任务,虽然执行的效率不一定很高,但是极大的缩短了程序设计、编写、调试的时间,因此非常适合快速学习、尝试、试错。 -本教程来自[IPython Notebooks to learn Python](https://github.com/rajathkmp/Python-Lectures),将其中部分示例代码转化成Python3。关于Python的按照可以自行去网络上查找相关的资料,或者参考[安装Python环境](../tips/InstallPython.md)。 +本教程来自[IPython Notebooks to learn Python](https://github.com/rajathkmp/Python-Lectures),将其中部分示例代码转化成Python3。关于Python的安装可以自行去网络上查找相关的资料,或者参考[安装Python环境](../tips/InstallPython.md)。 ## 内容 0. [Install Python](../tips/InstallPython.md) @@ -32,5 +32,6 @@ Python 是一门上手简单、功能强大、通用型的脚本编程语言。P * [IPython Notebooks to learn Python](https://github.com/rajathkmp/Python-Lectures) * [廖雪峰的Python教程](https://www.liaoxuefeng.com/wiki/1016959663602400) * [智能系统实验室入门教程-Python](https://gitee.com/pi-lab/SummerCamp/tree/master/python) -* [Python tips](../tips/python) +* [Python Tips](../tips/python) * [Get Started with Python](Python.pdf) +* [Python - 100天从新手到大师](https://github.com/jackfrued/Python-100-Days) \ No newline at end of file diff --git a/2_knn/knn_classification.ipynb b/2_knn/knn_classification.ipynb index ec88e27..1b60650 100644 --- a/2_knn/knn_classification.ipynb +++ b/2_knn/knn_classification.ipynb @@ -7,7 +7,7 @@ "# kNN Classification\n", "\n", "\n", - "K最近邻(k-Nearest Neighbor,kNN)分类算法,是一个理论上比较成熟的方法,也是最简单的机器学习算法之一。该方法的思路是:***如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)的样本中的大多数属于某一个类别,则该样本也属于这个类别***。kNN方法虽然从原理上也依赖于极限定理,但在类别决策时,只与极少量的相邻样本有关。由于kNN方法主要靠周围有限的邻近的样本,而不是靠判别类域的方法来确定所属类别的,因此对于类域的交叉或重叠较多的待分样本集来说,kNN方法较其他方法更为适合。\n", + "K最近邻(k-Nearest Neighbor,kNN)分类算法,是一个理论上比较成熟的方法,也是最简单的机器学习算法之一。该方法的思路是:***如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)的样本中的大多数属于某一个类别,则该样本也属于这个类别***。kNN方法虽然从原理上也依赖于[极限定理](https://baike.baidu.com/item/%E6%9E%81%E9%99%90%E5%AE%9A%E7%90%86/13672616),但在类别决策时,只与极少量的相邻样本有关。由于kNN方法主要靠周围有限的邻近的样本,而不是靠判别类域的方法来确定所属类别的,因此对于类域的交叉或重叠较多的待分样本集来说,kNN方法较其他方法更为适合。\n", "\n", "kNN算法不仅可以用于分类,还可以用于回归。通过找出一个样本的`k`个最近邻居,将这些邻居的属性的平均值赋给该样本,就可以得到该样本的属性。更有用的方法是将不同距离的邻居对该样本产生的影响给予不同的权值(weight),如权值与距离成正比(组合函数)。\n", "\n", @@ -45,12 +45,12 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 42, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", + "image/png": 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\n", 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" ] @@ -107,6 +107,7 @@ "x_test = x[split_index:]\n", "y_test = y[split_index:]\n", "\n", + "\n", "# visualize data\n", "plt.scatter(x_train[:,0], x_train[:,1], c=y_train, marker='.')\n", "plt.title(\"train data\")\n", @@ -120,12 +121,109 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## 3. Program" + "## 3. Simple Program" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1]\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "import operator\n", + "\n", + "def knn_distance(v1, v2):\n", + " return np.sum(np.square(v1-v2))\n", + "\n", + "def knn_vote(ys):\n", + " vote_dict = {}\n", + " for y in ys:\n", + " if y not in vote_dict.keys():\n", + " vote_dict[y] = 1\n", + " else:\n", + " vote_dict[y] += 1\n", + " sorted_vote_dict = sorted(vote_dict.items(), \\\n", + " key=operator.itemgetter(1), \\\n", + " reverse=True)\n", + " return sorted_vote_dict[0][0]\n", + " \n", + "def knn_predict(x, train_x, train_y, k=3):\n", + " dist_arr = [knn_distance(x, train_x[j]) for j in range(len(train_x))]\n", + " sorted_index = np.argsort(dist_arr)\n", + " top_k_index = sorted_index[:k]\n", + " ys=train_y[top_k_index]\n", + " return knn_vote(ys)\n", + " \n", + "\n", + "#a = knn_predict(x_train[0], x_train, y_train)\n", + "y_train_est = [knn_predict(x_train[i], x_train, y_train) for i in range(len(x_train))]\n", + "print(y_train_est)" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Train Accuracy: 98.568507%\n" + ] + } + ], + "source": [ + "n_correct = 0\n", + "for i in range(len(x_train)):\n", + " if y_train_est[i] == y_train[i]:\n", + " n_correct += 1\n", + "accuracy = n_correct / len(x_train) * 100.0\n", + "print(\"Train Accuracy: %f%%\" % accuracy)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test Accuracy: 95.734597%\n" + ] + } + ], + "source": [ + "y_test_est = [knn_predict(x_test[i], x_train, y_train, 3) for i in range(len(x_test))]\n", + "n_correct = 0\n", + "for i in range(len(x_test)):\n", + " if y_test_est[i] == y_test[i]:\n", + " n_correct += 1\n", + "accuracy = n_correct / len(x_test) * 100.0\n", + "print(\"Test Accuracy: %f%%\" % accuracy)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Complex Program" + ] + }, + { + "cell_type": "code", + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ @@ -140,6 +238,7 @@ " def fit(self, x, y):\n", " self.x = x\n", " self.y = y\n", + " return self\n", "\n", " def _square_distance(self, v1, v2):\n", " return np.sum(np.square(v1-v2))\n", @@ -178,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 44, "metadata": {}, "outputs": [ { @@ -186,18 +285,18 @@ "output_type": "stream", "text": [ "train accuracy: 0.986\n", - "test accuracy: 0.957\n" + "test accuracy: 0.967\n" ] } ], "source": [ "# data preprocessing\n", - "x_train = (x_train - np.min(x_train, axis=0)) / (np.max(x_train, axis=0) - np.min(x_train, axis=0))\n", - "x_test = (x_test - np.min(x_test, axis=0)) / (np.max(x_test, axis=0) - np.min(x_test, axis=0))\n", + "#x_train = (x_train - np.min(x_train, axis=0)) / (np.max(x_train, axis=0) - np.min(x_train, axis=0))\n", + "#x_test = (x_test - np.min(x_test, axis=0)) / (np.max(x_test, axis=0) - np.min(x_test, axis=0))\n", "\n", "# knn classifier\n", "clf = KNN(k=3)\n", - "clf.fit(x_train, y_train)\n", + "acc = clf.fit(x_train, y_train).score()\n", "\n", "print('train accuracy: {:.3}'.format(clf.score()))\n", "\n", @@ -214,7 +313,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -227,7 +326,7 @@ } ], "source": [ - "% matplotlib inline\n", + "#% matplotlib inline\n", "\n", "import matplotlib.pyplot as plt\n", "from sklearn import datasets, neighbors, linear_model\n", @@ -243,12 +342,12 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { - "image/png": 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+ "image/png": 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\n", 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" ] @@ -272,7 +371,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -288,7 +387,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -296,7 +395,21 @@ "output_type": "stream", "text": [ "KNN score: 0.953661\n", - "LogisticRegression score: 0.908248\n" + "LogisticRegression score: 0.927711\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/bushuhui/virtualenv/dl/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:764: ConvergenceWarning: lbfgs failed to converge (status=1):\n", + "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", + "\n", + "Increase the number of iterations (max_iter) or scale the data as shown in:\n", + " https://scikit-learn.org/stable/modules/preprocessing.html\n", + "Please also refer to the documentation for alternative solver options:\n", + " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", + " extra_warning_msg=_LOGISTIC_SOLVER_CONVERGENCE_MSG)\n" ] } ],