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- # -*- coding: utf-8 -*-
- """
- @author: yq
- @time: 2024/11/27
- @desc:
- """
- import time
- from entitys import DataSplitEntity, MlConfigEntity
- from pipeline import Pipeline
- if __name__ == "__main__":
- time_now = time.time()
- import scorecardpy as sc
- # 加载数据
- dat = sc.germancredit()
- dat_columns = dat.columns.tolist()
- dat_columns = [c.replace(".","_") for c in dat_columns]
- dat.columns = dat_columns
- dat["creditability"] = dat["creditability"].apply(lambda x: 1 if x == "bad" else 0)
- data = DataSplitEntity(train_data=dat[:709], test_data=dat[709:])
- # 训练并生成报告
- train_pipeline = Pipeline(MlConfigEntity.from_config('./config/ml_config_template.json'), data)
- train_pipeline.train()
- train_pipeline.report()
- print(time.time() - time_now)
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