基于自定义数据集利用catboost 算法实现回归预测(训练采用CPU和GPU两种方式)

输出结果

# T1、训练采用CPU

0:   learn: 7.9608417    total: 50.2ms   remaining: 1.46s
1:  learn: 7.7618206    total: 50.5ms   remaining: 707ms
2:  learn: 7.5879985    total: 50.9ms   remaining: 458ms
3:  learn: 7.4148674    total: 51.4ms   remaining: 334ms
4:  learn: 7.2488388    total: 51.6ms   remaining: 258ms
5:  learn: 7.0676178    total: 51.8ms   remaining: 207ms
6:  learn: 6.8909273    total: 51.9ms   remaining: 171ms
7:  learn: 6.7186541    total: 52.1ms   remaining: 143ms
8:  learn: 6.5506878    total: 52.3ms   remaining: 122ms
9:  learn: 6.3869206    total: 52.4ms   remaining: 105ms
10: learn: 6.2272476    total: 52.6ms   remaining: 90.9ms
11: learn: 6.0715664    total: 52.8ms   remaining: 79.2ms
12: learn: 5.9197772    total: 52.9ms   remaining: 69.2ms
13: learn: 5.7717828    total: 53.1ms   remaining: 60.7ms
14: learn: 5.6274882    total: 53.2ms   remaining: 53.2ms
15: learn: 5.4868010    total: 53.4ms   remaining: 46.7ms
16: learn: 5.3496310    total: 53.6ms   remaining: 41ms
17: learn: 5.2158902    total: 53.7ms   remaining: 35.8ms
18: learn: 5.0854930    total: 53.9ms   remaining: 31.2ms
19: learn: 4.9583556    total: 54ms remaining: 27ms
20: learn: 4.8343967    total: 54.2ms   remaining: 23.2ms
21: learn: 4.7135368    total: 54.4ms   remaining: 19.8ms
22: learn: 4.5956984    total: 54.5ms   remaining: 16.6ms
23: learn: 4.4808059    total: 54.7ms   remaining: 13.7ms
24: learn: 4.3687858    total: 54.9ms   remaining: 11ms
25: learn: 4.2595661    total: 55ms remaining: 8.46ms
26: learn: 4.1530770    total: 55.2ms   remaining: 6.13ms
27: learn: 4.0492501    total: 55.3ms   remaining: 3.95ms
28: learn: 3.9480188    total: 55.5ms   remaining: 1.91ms
29: learn: 3.8493183    total: 55.7ms   remaining: 0us
[14.72696421 19.90303684]

# T2、训练采用GPU

0:   learn: 7.9608417    total: 114ms    remaining: 3.29s
1:  learn: 7.7618210    total: 118ms    remaining: 1.65s
2:  learn: 7.5677758    total: 122ms    remaining: 1.1s
3:  learn: 7.3785819    total: 125ms    remaining: 814ms
4:  learn: 7.1941178    total: 128ms    remaining: 642ms
5:  learn: 7.0142648    total: 132ms    remaining: 529ms
6:  learn: 6.8389078    total: 136ms    remaining: 446ms
7:  learn: 6.6679348    total: 140ms    remaining: 385ms
8:  learn: 6.5012368    total: 143ms    remaining: 335ms
9:  learn: 6.3387062    total: 149ms    remaining: 297ms
10: learn: 6.1802387    total: 153ms    remaining: 264ms
11: learn: 6.0257332    total: 156ms    remaining: 234ms
12: learn: 5.8750898    total: 162ms    remaining: 212ms
13: learn: 5.7282121    total: 166ms    remaining: 190ms
14: learn: 5.5850064    total: 171ms    remaining: 171ms
15: learn: 5.4453814    total: 175ms    remaining: 153ms
16: learn: 5.3092462    total: 180ms    remaining: 137ms
17: learn: 5.1765153    total: 184ms    remaining: 122ms
18: learn: 5.0471030    total: 188ms    remaining: 109ms
19: learn: 4.9209255    total: 193ms    remaining: 96.3ms
20: learn: 4.7979018    total: 196ms    remaining: 84.2ms
21: learn: 4.6779541    total: 200ms    remaining: 72.7ms
22: learn: 4.5610056    total: 204ms    remaining: 62.1ms
23: learn: 4.4469804    total: 208ms    remaining: 51.9ms
24: learn: 4.3358058    total: 212ms    remaining: 42.5ms
25: learn: 4.2274105    total: 218ms    remaining: 33.6ms
26: learn: 4.1217256    total: 223ms    remaining: 24.8ms
27: learn: 4.0186824    total: 227ms    remaining: 16.2ms
28: learn: 3.9182151    total: 230ms    remaining: 7.95ms
29: learn: 3.8202597    total: 235ms    remaining: 0us
[14.67884178 20.        ]

实现代码

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

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ML之catboost：基于自定义数据集利用catboost 算法实现回归预测(训练采用CPU和GPU两种方式)

基于自定义数据集利用catboost 算法实现回归预测(训练采用CPU和GPU两种方式)

输出结果

# T1、训练采用CPU

# T2、训练采用GPU

实现代码

ML之catboost：基于自定义数据集利用catboost 算法实现回归预测(训练采用CPU和GPU两种方式)相关推荐

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