获取 rov 数据

main.py

@@ -113,7 +113,7 @@ class LightGBM(object):
         :return:
         """
         path = "data/train_data/all_train_20240409.json"
-        x, y, ori_df = self.read_data(path, yc=0.035)
+        x, y, ori_df = self.read_data(path, yc=0.05)
         train_size = int(len(x) * self.split_c)
         X_train, X_test = x[:train_size], x[train_size:]
         Y_train, Y_test = y[:train_size], y[train_size:]
@@ -147,7 +147,7 @@ class LightGBM(object):
         """
         fw = open("result/summary_{}.txt".format(dt), "a+", encoding="utf-8")
         path = 'data/predict_data/all_predict_{}.json'.format(dt)
-        x, y, ori_df = self.read_data(path, yc=0.035)
+        x, y, ori_df = self.read_data(path, yc=0.05)
         true_label_df = pd.DataFrame(list(y), columns=['ture_label'])
         bst = lgb.Booster(model_file=self.model)
         y_pred = bst.predict(x, num_iteration=bst.best_iteration)
@@ -194,6 +194,7 @@ class LightGBM(object):
 # "cat summary_20240326.txt | awk -F "\t" '{print $1" "$3}'| /root/AUC/AUC/AUC"
 """
  ossutil64 cp /root/luojunhui/alg/data/predict_data/spider_predict_result_20240330.xlsx oss://art-pubbucket/0temp/
+ cat summary_20240326.txt | awk -F "\t" '{print $1" "$3}'| /root/AUC/AUC/AUC
  cat summary_20240327.txt | awk -F "\t" '{print $1" "$3}'| /root/AUC/AUC/AUC
 """
 if __name__ == "__main__":