19 lines
644 B
Python
19 lines
644 B
Python
from numpy import loadtxt
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.layers import Dense
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dataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')
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x = dataset[:-50,0:8]
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y = dataset[:-50,8]
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x_test = dataset[-50:,0:8]
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y_test = dataset[-50:,8]
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model = Sequential()
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model.add(Dense(12, input_shape=(8,), activation='relu'))
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model.add(Dense(8, activation='relu'))
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model.add(Dense(1, activation='sigmoid'))
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model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
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model.fit(x, y, epochs=150, batch_size=10)
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_, accuracy = model.evaluate(x_test, y_test)
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print('Accuracy: %.2f' % (accuracy*100))
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