关于采用其他数据集测试后，模型性能提升效果不好的问题 about evolutionaryforest

[hengzhe-zhang]

您好，感谢您使用算法包。建议您分出来一部分数据作为验证集，观测一下是否存在过拟合现象。如果存在过拟合现象的话，需要使用Early Stopping机制。

X, y = load_diabetes(return_X_y=True)
train_X, test_X, train_y, test_y = train_test_split(X, y, test_size=0.2, random_state=0)
train_X, val_X, train_y, val_y = train_test_split(train_X, train_y, test_size=0.2, random_state=0)
reg = EvolutionaryForestRegressor(max_height=3, normalize=True, select='AutomaticLexicase',
                                  gene_num=10, boost_size=100, n_gen=20, n_pop=200, cross_pb=1,
                                  base_learner='Random-DT', verbose=True)
reg.test_fun = [TestFunction(train_X, train_y, reg), TestFunction(val_X, val_y, reg)]
reg.fit(train_X, train_y)

[hengzhe-zhang]

如果您有后续反馈，欢迎重新开启issue。