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import os.path |
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import numpy as np |
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import pandas as pd |
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import argparse |
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from sklearn.metrics import roc_auc_score |
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parser = argparse.ArgumentParser() |
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parser.add_argument('--path', type=str, required=True) |
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parser.add_argument('--name', type=str, required=True) |
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parser.add_argument('--answer_file', type=str, required=True) |
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parser.add_argument('--predict_file', type=str, required=True) |
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parser.add_argument('--value', type=str, default="Attrition") |
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args = parser.parse_args() |
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actual = pd.read_csv(args.answer_file) |
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submission = pd.read_csv(args.predict_file) |
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actual.sort_values(by=actual.columns[0]) |
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submission.sort_values(by=submission.columns[0]) |
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performance = roc_auc_score(actual[args.value], submission[args.value]) |
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with open(os.path.join(args.path, args.name, "result.txt"), "w") as f: |
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f.write(str(performance)) |
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