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@@ -145,7 +145,7 @@ class LightGBM(object):
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X_test[key] = pd.to_numeric(X_test[key], errors="coerce")
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bst = lgb.Booster(model_file=self.model)
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y_pred = bst.predict(X_test, num_iteration=bst.best_iteration)
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- y_pred_binary = [0 if i <= 0.158550 else 1 for i in list(y_pred)]
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+ y_pred_binary = [0 if i <= 0.162294 else 1 for i in list(y_pred)]
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# 转换为二进制输出
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score_list = []
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for index, item in enumerate(list(y_pred)):
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@@ -181,6 +181,6 @@ class LightGBM(object):
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if __name__ == "__main__":
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L = LightGBM()
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- L.train_model()
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+ # L.train_model()
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L.evaluate_model()
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- L.feature_importance()
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+ # L.feature_importance()
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