输出预测结果

浙江行业电量/分类归一化.py

@@ -95,8 +95,8 @@ for industry in df.columns[2:][1:]:
 print(dataset_x.shape, dataset_y.shape)
 
 train_size = int(0.7 * len(dataset_x))
-x_train, y_train = dataset_x[:train_size], dataset_y[:train_size]
+x_train, y_train = dataset_x[:train_size].reshape(-1,1,10), dataset_y[:train_size].reshape(-1, 1, 3)
-x_eval, y_eval = dataset_x[train_size:], dataset_y[train_size:]
+x_eval, y_eval = dataset_x[train_size:].reshape(-1,1,10), dataset_y[train_size:].reshape(-1, 1, 3)
 x_train, y_train = torch.from_numpy(x_train).type(torch.float32), torch.from_numpy(y_train).type(torch.float32)
 x_eval, y_eval = torch.from_numpy(x_eval).type(torch.float32), torch.from_numpy(y_eval).type(torch.float32)