{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# 读入数据,获得输入X和输出Y\n", "import pandas as pd\n", "data=pd.read_csv('5_train_regression.csv')\n", "X = data.drop(columns='Y', inplace=False)\n", "Y = data.get('Y')\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# 数据预处理,将原始数据标准化\n", "from sklearn.preprocessing import StandardScaler\n", "scaler = StandardScaler()\n", "scaler.fit(X)\n", "X_std = scaler.transform(X)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# 5次5折交叉验证\n", "from sklearn.model_selection import RepeatedKFold\n", "rkf = RepeatedKFold(n_splits=5, n_repeats=5, random_state=0) #种子设为0" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MAPE: 0.20673280973822433\n" ] } ], "source": [ "# 创建神经网络模型\n", "from sklearn.neural_network import MLPRegressor\n", "from sklearn.model_selection import cross_val_score\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "mlp = MLPRegressor(hidden_layer_sizes=(100), activation='relu', solver='adam', alpha=0.0001, batch_size='auto', learning_rate='constant', learning_rate_init=0.001, power_t=0.5, max_iter=200, shuffle=True, random_state=None, tol=0.0001, verbose=False, warm_start=False, momentum=0.9, nesterovs_momentum=True, early_stopping=False, validation_fraction=0.1, beta_1=0.9, beta_2=0.999, epsilon=1e-08, n_iter_no_change=10, max_fun=15000) #所有参数默认\n", "mlp.fit(X_std, Y)\n", "MAPE = -1*cross_val_score(mlp, X_std, Y, cv=rkf,scoring='neg_mean_absolute_percentage_error').mean()\n", "print('MAPE:',MAPE)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "最优参数: {'activation': 'relu', 'alpha': 1, 'hidden_layer_sizes': (100, 100, 100, 100, 100), 'learning_rate': 'adaptive', 'solver': 'sgd'}\n", "最优模型得分: -0.10669120458358475\n" ] } ], "source": [ "# 超参数调优\n", "import warnings\n", "warnings.filterwarnings('ignore')\n", "from sklearn.model_selection import GridSearchCV\n", "parameters = {'hidden_layer_sizes': [(10,10,10,10,10),(20,20,20,20,20),(30,30,30,30,30),(40,40,40,40,40),(50,50,50,50,50),(60,60,60,60,60),(70,70,70,70,70),(80,80,80,80,80),(90,90,90,90,90),(100,100,100,100,100)],\n", " 'activation': ['identity', 'logistic','tanh', 'relu'],\n", " 'solver': ['adam','lbgfs','sgd'],\n", " 'alpha': [0.0001, 0.001, 0.01, 0.1, 1,10,100],\n", " 'learning_rate': ['constant', 'invscaling', 'adaptive']}\n", "grid = GridSearchCV(mlp, parameters, cv=rkf, scoring='neg_mean_absolute_percentage_error',n_jobs=-1)\n", "grid.fit(X_std, Y)\n", "print('最优参数:',grid.best_params_)\n", "print('最优模型得分:',grid.best_score_)\n" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['mlp_regression.pkl']" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 保存模型\n", "import joblib\n", "joblib.dump(grid.best_estimator_, 'mlp_regression.pkl')" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# 读取模型\n", "import joblib\n", "mlp_regression = joblib.load('mlp_regression.pkl')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from yellowbrick.regressor import ResidualsPlot\n", "from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X_std, Y, test_size=0.2)\n", "visualizer = ResidualsPlot(mlp_regression)\n", "visualizer.fit(X_train, y_train) \n", "visualizer.score(X_test, y_test) \n", "g = visualizer.poof() # 查看残差图" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from yellowbrick.regressor import PredictionError\n", "visualizer = PredictionError(mlp_regression)\n", "visualizer.fit(X_train, y_train)\n", "visualizer.score(X_test, y_test)\n", "g = visualizer.poof() # 查看预测误差图" ] } ], "metadata": { "interpreter": { "hash": "cc5f70855ac006f3de45a3cc3b9e7d8d53845e50458809cb162b0174266dec97" }, "kernelspec": { "display_name": "Python 3.7.0 64-bit ('base': conda)", "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": "3.8.8" }, "orig_nbformat": 4 }, "nbformat": 4, "nbformat_minor": 2 }