Final commit of the exercise 6
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@ -4,6 +4,7 @@ from sklearn.metrics import accuracy_score, classification_report
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import pandas as pd
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from sklearn.model_selection import train_test_split
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import numpy as np
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import sys
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from sklearn.preprocessing import StandardScaler, LabelEncoder
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from tensorflow.keras.optimizers import Adam
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@ -45,6 +46,6 @@ rms = Adam(lr=0.0003)
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NeuralModel.compile(optimizer=rms, loss='binary_crossentropy', metrics=['accuracy'])
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NeuralModel.fit(scaled_x, yenc, epochs=15) #verbose = 1
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NeuralModel.fit(scaled_x, yenc, batch_size=int(sys.argv[1]), epochs = int(sys.argv[1])) #verbose = 1
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NeuralModel.save('wine_model.h5')
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