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31. [14.67884178 20.        ]

1. # ML之catboost：基于自定义数据集实现回归预测
2. from catboost import CatBoostRegressor
3. 
4. #1、定义数据集
5. train_data = [[12, 14, 16, 18], 
6.               [23, 25, 27, 29], 
7.               [32, 34, 36, 38]]
8. train_labels = [10, 20, 30]
9. 
10. eval_data = [[2, 4, 6, 8], 
11.              [20, 21, 24, 33]]
12. 
13. #2、模型预测
14. model_CatBR = CatBoostRegressor(iterations=30, learning_rate=0.1, depth=2)
15. model_CatBR.fit(train_data, train_labels)
16. preds = model_CatBR.predict(eval_data)
17. print(preds)