fix
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30c8343c6c
commit
069a5860d6
4
train.py
4
train.py
@ -40,10 +40,8 @@ def prepare_model(epoch_param, batch_param, _run):
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X_train = vgsales_train.drop(['Rank','Name','Platform','Year','Genre','Publisher'],axis = 1)
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X_train = vgsales_train.drop(['Rank','Name','Platform','Year','Genre','Publisher'],axis = 1)
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y_train = vgsales_train[['Nintendo']]
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y_train = vgsales_train[['Nintendo']]
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y_train = keras.utils.to_categorical(y_train)
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X_test = vgsales_test.drop(['Rank','Name','Platform','Year','Genre','Publisher'],axis = 1)
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X_test = vgsales_test.drop(['Rank','Name','Platform','Year','Genre','Publisher'],axis = 1)
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y_test = vgsales_test[['Nintendo']]
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y_test = vgsales_test[['Nintendo']]
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y_test = keras.utils.to_categorical(y_test)
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print(X_train.shape[1])
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print(X_train.shape[1])
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@ -53,7 +51,7 @@ def prepare_model(epoch_param, batch_param, _run):
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early_stop = EarlyStopping(monitor="val_loss", mode="min", verbose=1, patience=10)
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early_stop = EarlyStopping(monitor="val_loss", mode="min", verbose=1, patience=10)
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model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
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model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
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epochs = int(sys.argv[1])
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epochs = int(sys.argv[1])
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batch_size = int(sys.argv[2])
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batch_size = int(sys.argv[2])
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