wizardforcel · zcxboy · Jun 27, 2023 · Jun 27, 2023 · Jun 28, 2023 · Jul 14, 2023
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diff --git a/sicp/Exercises/1.1.ipynb b/sicp/Exercises/1.1.ipynb
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+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 引言"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "预测2023年全国高考录取率为： 45.64666666666653\n",
+      "预测2023年湖北省本科录取率为： 45.64666666666653\n",
+      "预测2023年湖北省一本录取率为： 16.953333333333333\n",
+      "预测2023年湖北省211录取率为： 5.280000000000001\n",
+      "预测2023年湖北省985录取率为： 2.153333333333336\n",
+      "预测2023年湖北省本科录取人数为： 219103.99999999936\n",
+      "预测2023年湖北省一本录取人数为： 81376.0\n",
+      "预测2023年湖北省211录取人数为： 25344.000000000004\n",
+      "预测2023年湖北省985录取人数为： 10336.000000000013\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.linear_model import LinearRegression\n",
+    "\n",
+    "# 假设您已经获得了2020-2022年的湖北高考录取率数据，存储在一个Pandas DataFrame中\n",
+    "data = {'年份': [2020, 2021, 2022],\n",
+    "        '本科录取率': [42.1, 45.14, 44],\n",
+    "        '一本录取率': [15.8, 18.9, 15.89],\n",
+    "        '211录取率': [5.2, 5.6, 5.16],\n",
+    "        '985录取率': [2.1, 2.1, 2.14]}\n",
+    "df = pd.DataFrame(data)\n",
+    "\n",
+    "# 使用线性回归模型拟合数据\n",
+    "X = df[['年份']]\n",
+    "y1 = df['本科录取率']\n",
+    "y2 = df['一本录取率']\n",
+    "y3 = df['211录取率']\n",
+    "y4 = df['985录取率']\n",
+    "model1 = LinearRegression().fit(X, y1)\n",
+    "model2 = LinearRegression().fit(X, y2)\n",
+    "model3 = LinearRegression().fit(X, y3)\n",
+    "model4 = LinearRegression().fit(X, y4)\n",
+    "\n",
+    "# 预测2023年的录取率\n",
+    "this_year = pd.DataFrame({'年份': [2023]})\n",
+    "predicted_本科录取率 = model1.predict(this_year)[0]\n",
+    "predicted_一本录取率 = model2.predict(this_year)[0]\n",
+    "predicted_211录取率 = model3.predict(this_year)[0]\n",
+    "predicted_985录取率 = model4.predict(this_year)[0]\n",
+    "\n",
+    "# 计算全国录取率\n",
+    "全国高考报名人数 = 12910000\n",
+    "湖北高考人数 = 480000\n",
+    "全国录取人数 = 全国高考报名人数 * predicted_本科录取率 / 100\n",
+    "湖北本科录取人数 = 湖北高考人数 * predicted_本科录取率 / 100\n",
+    "湖北一本录取人数 = 湖北高考人数 * predicted_一本录取率 / 100\n",
+    "湖北211录取人数 = 湖北高考人数 * predicted_211录取率 / 100\n",
+    "湖北985录取人数 = 湖北高考人数 * predicted_985录取率 / 100\n",
+    "全国录取率 = 全国录取人数 / 全国高考报名人数 * 100\n",
+    "\n",
+    "# 输出结果\n",
+    "print('预测2023年全国高考录取率为：', 全国录取率)\n",
+    "print('预测2023年湖北省本科录取率为：', predicted_本科录取率)\n",
+    "print('预测2023年湖北省一本录取率为：', predicted_一本录取率)\n",
+    "print('预测2023年湖北省211录取率为：', predicted_211录取率)\n",
+    "print('预测2023年湖北省985录取率为：', predicted_985录取率)\n",
+    "print('预测2023年湖北省本科录取人数为：', 湖北本科录取人数)\n",
+    "print('预测2023年湖北省一本录取人数为：', 湖北一本录取人数)\n",
+    "print('预测2023年湖北省211录取人数为：', 湖北211录取人数)\n",
+    "print('预测2023年湖北省985录取人数为：', 湖北985录取人数)"
+   ]
+  }
+ ],
+ "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": "3.10.8"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
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