From a0be2abc81a48646a23280f2947ef1f9ce99fecb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E9=83=AD=E7=BE=BD?= <guoyu@igengmei.com> Date: Wed, 26 May 2021 19:26:47 +0800 Subject: [PATCH] =?UTF-8?q?=E7=BE=8E=E8=B4=AD=E7=B2=BE=E6=8E=92=E6=A8=A1?= =?UTF-8?q?=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- mlp/train.py | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/mlp/train.py b/mlp/train.py index d73ae4e..d8cd1a8 100644 --- a/mlp/train.py +++ b/mlp/train.py @@ -39,18 +39,18 @@ def getDataVocabFromRedis(version): return dataVocab # æ•°æ®ç±»åž‹è½¬æ¢ -def csvTypeConvert(df,data_vocab): - # 离散na值填充 - for k, v in data_vocab.items(): - df[k] = df[k].fillna("-1") - df[k] = df[k].astype("string") - - for k in ITEM_NUMBER_COLUMNS: - df[k] = df[k].fillna(0.0) - df[k] = df[k].astype("float") +def csvTypeConvert(columns,df,data_vocab): + for k in columns: + # 离散na值填充 + if k in data_vocab.items(): + df[k] = df[k].astype("string") + df[k] = df[k].fillna("-1") + else: + df[k] = df[k].astype("float") + df[k] = df[k].fillna(0.0) df["label"] = df["label"].astype("int") - print(df.dtypes) + # print(df.dtypes) return df def loadData(data_path): @@ -166,8 +166,8 @@ if __name__ == '__main__': print("trainSize:{},testSize{}".format(trainSize,testSize)) # æ•°æ®ç±»åž‹è½¬æ¢ - df_train = csvTypeConvert(df_train,data_vocab) - df_test = csvTypeConvert(df_test,data_vocab) + df_train = csvTypeConvert(datasColumns,df_train,data_vocab) + df_test = csvTypeConvert(datasColumns,df_test,data_vocab) # 获å–è®ç»ƒæ•°æ® train_data = getDataSet(df_train,shuffleSize=trainSize,) -- 2.18.0