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@ -6,7 +6,7 @@ import sys
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import matplotlib.pyplot as plt
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from sklearn.metrics import accuracy_score, classification_report
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model = keras.models.load_model('saved_model.pb')
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model = keras.models.load_model('wine_model.h5')
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print('evaluating')
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test_df =pd.read_csv('test.csv')
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@ -33,4 +33,4 @@ def regression_model():
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model = regression_model()
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model.fit(x_train, y_train, batch_size=int(sys.argv[1]), epochs = int(sys.argv[1])) #verbose = 1
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model.save('wine_model')
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model.save('wine_model.h5')
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