构建函数 - 画学习曲线learning curves| Python

from sklearn.metrics import mean_square_error from sklearn.model_selection import train_test_split import numpy as np import matplotlib.pyplot as plt def plot_learning_curves(model, X, y): """ 画学习曲线 parameters ---------- model: 模型 X：特征值 y：目标量 """ X_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.2) train_errors, val_errors = [], [] for m in range(1, len(X_train)): model.fit(X_train[:m], y_train[:m]) y_train_predict = model.predict(X_train[:m]) y_val_predict = model.predict(X_val) train_errors.append(mean_square_error(y_train_predict, y_train[:m])) val_errors.append(mean_square_error(y_val_predict, y_val)) plt.plot(nq.sqrt(train_errors), "r-+", linewidth=2, label="train") plt.plot(np.sqrt(val_errors), "b-", linewidth=3, label="val") plt.legend(loc="upper right", fontsize=14) plt.xlabe("Training set size", fontsize=14) plt.ylabel("RMSE", fontsize=14)