复制 import numpy as npfrom sklearn.tree import DecisionTreeClassifierclass SimpleRandomForest:def __init__(self， y_boot = X[idx]。
feat_idx]，。
y[idx]# 随机选特征feat_idx = np.random.choice(n_features。
self.feature_indices[i]])predictions.append(pred)# 多数投票return np.array([np.bincount(col).argmax() for col in np.array(predictions).T]) ， X， X):predictions = []for i， replace=False)self.feature_indices.append(feat_idx)# 训练树tree = DecisionTreeClassifier()tree.fit(X_boot[:， n_estimators=10， n_features = X.shapeif self.max_features == sqrt:m = int(np.sqrt(n_features))else:m = n_features // 3for _ in range(self.n_estimators):# Bootstrap 采样idx = np.random.choice(n_samples， tree in enumerate(self.trees):pred = tree.predict(X[:， y):n_samples， replace=True)X_boot， m， n_samples， y_boot)self.trees.append(tree)def predict(self， max_features=sqrt):self.n_estimators = n_estimatorsself.max_features = max_featuresself.trees = []self.feature_indices = []def fit(self。