From 11630bfcce467c6856a03cbeb6277bbf85c45ff3 Mon Sep 17 00:00:00 2001 From: liurui Date: Fri, 6 Dec 2024 11:18:45 +0800 Subject: [PATCH] =?UTF-8?q?=E5=8E=9F=E6=B2=B9=E7=94=BB=E5=9B=BE=E8=BE=B9?= =?UTF-8?q?=E7=95=8C=E5=88=A4=E6=96=AD20=E6=94=B9=E4=B8=BA60?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- main_yuanyou.py | 38 ++++++++++++++++++------------------ models/nerulforcastmodels.py | 6 +++--- 2 files changed, 22 insertions(+), 22 deletions(-) diff --git a/main_yuanyou.py b/main_yuanyou.py index 2ca77c8..8900fad 100644 --- a/main_yuanyou.py +++ b/main_yuanyou.py @@ -172,25 +172,25 @@ def predict_main(): row, col = df.shape now = datetime.datetime.now().strftime('%Y%m%d%H%M%S') - # ex_Model(df, - # horizon=horizon, - # input_size=input_size, - # train_steps=train_steps, - # val_check_steps=val_check_steps, - # early_stop_patience_steps=early_stop_patience_steps, - # is_debug=is_debug, - # dataset=dataset, - # is_train=is_train, - # is_fivemodels=is_fivemodels, - # val_size=val_size, - # test_size=test_size, - # settings=settings, - # now=now, - # etadata=etadata, - # modelsindex=modelsindex, - # data=data, - # is_eta=is_eta, - # ) + ex_Model(df, + horizon=horizon, + input_size=input_size, + train_steps=train_steps, + val_check_steps=val_check_steps, + early_stop_patience_steps=early_stop_patience_steps, + is_debug=is_debug, + dataset=dataset, + is_train=is_train, + is_fivemodels=is_fivemodels, + val_size=val_size, + test_size=test_size, + settings=settings, + now=now, + etadata=etadata, + modelsindex=modelsindex, + data=data, + is_eta=is_eta, + ) logger.info('模型训练完成') diff --git a/models/nerulforcastmodels.py b/models/nerulforcastmodels.py index 5991c30..8dbe22e 100644 --- a/models/nerulforcastmodels.py +++ b/models/nerulforcastmodels.py @@ -353,11 +353,11 @@ def model_losss(sqlitedb): def find_most_common_model(): # 最多频率的模型名称 - min_model_max_frequency_model = df_combined3['min_model'].tail(20).value_counts().idxmax() - max_model_max_frequency_model = df_combined3['max_model'].tail(20).value_counts().idxmax() + min_model_max_frequency_model = df_combined3['min_model'].tail(60).value_counts().idxmax() + max_model_max_frequency_model = df_combined3['max_model'].tail(60).value_counts().idxmax() if min_model_max_frequency_model == max_model_max_frequency_model: # 取20天第二多的模型 - max_model_max_frequency_model = df_combined3['max_model'].tail(20).value_counts().nlargest(2).index[1] + max_model_max_frequency_model = df_combined3['max_model'].tail(60).value_counts().nlargest(2).index[1] df_predict['min_model'] = min_model_max_frequency_model df_predict['max_model'] = max_model_max_frequency_model