40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import pandas as pd
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import sys
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import tensorflow
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from tensorflow.keras import layers
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X_train = pd.read_csv('train.csv')
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X_test = pd.read_csv('test.csv')
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X_valid = pd.read_csv('valid.csv')
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Y_train = X_train.pop('stabf')
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Y_train = pd.get_dummies(Y_train)
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Y_test = X_test.pop('stabf')
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Y_test = pd.get_dummies(Y_test)
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Y_valid = X_valid.pop('stabf')
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Y_valid = pd.get_dummies(Y_valid)
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# model = tensorflow.keras.Sequential([
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# layers.Input(shape=(12,)),
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# layers.Dense(32),
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# layers.Dense(16),
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# layers.Dense(2, activation='softmax')
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# ])
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model = tensorflow.keras.Sequential()
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model.add(layers.Input(shape=(12,)))
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model.add(layers.Dense(32))
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model.add(layers.Dense(16))
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model.add(layers.Dense(2, activation='softmax'))
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model.compile(
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loss=tensorflow.keras.losses.BinaryCrossentropy(),
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optimizer=tensorflow.keras.optimizers.Adam(lr=float(sys.argv[1])),
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metrics=[tensorflow.keras.metrics.BinaryAccuracy()])
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history = model.fit(X_train, Y_train, epochs=2, validation_data=(X_valid, Y_valid))
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model.save('grid-stability-dense.h5')
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