{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from sklearn import linear_model\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"\n",
"np.random.seed(1220)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# 生成模型数据\n",
"size = 10000\n",
"x = np.random.normal(size=size)\n",
"y = (x > 0).astype(np.float64)\n",
"x *= 1.5\n",
"x += 0.5 * np.random.normal(size=size)\n",
"x = x[:, np.newaxis]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"LinearRegression() In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. "
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# 为在Matplotlib中显示中文，设置特殊字体\n",
"plt.rcParams['font.sans-serif'] = ['SimHei']\n",
"# 正确显示负号\n",
"plt.rcParams['axes.unicode_minus'] = False\n",
"plt.rcParams.update({'font.size': 13})\n",
"# 创建一个图形框，在里面画两幅画\n",
"fig = plt.figure(figsize=(12, 6), dpi=100)\n",
"ax = fig.add_subplot(1, 2, 1)\n",
"ax.set_xlabel('$x$')\n",
"ax.set_ylabel('$y$')\n",
"# 将原始数据表现在图上\n",
"ax.scatter(x[:40], y[:40], color='black')\n",
"# 画拟合的直线\n",
"xline = np.linspace(-3, 5, 100)[:, np.newaxis]\n",
"yline = model.predict(xline)\n",
"ax.plot(xline.ravel(), yline, 'r')\n",
"# 第二幅图\n",
"ax1 = fig.add_subplot(1, 2, 2)\n",
"residual = y - model.predict(x)\n",
"n, bins, _ = ax1.hist(residual, 40, density=1, facecolor='grey', rwidth=0.8, alpha=0.6)\n",
"# 用多项式拟合得到的直方图\n",
"z1 = np.polyfit(bins[:-1], n, 10)\n",
"p1 = np.poly1d(z1)\n",
"ax1.plot(bins[:-1], p1(bins[:-1]), 'r-.')\n",
"ax1.set_xlabel('$residual$')\n",
"plt.savefig('logit_example.png', dpi=200)\n",
"plt.show()"
]
}
],
"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": "3.8.5"
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"nbformat": 4,
"nbformat_minor": 4
}