37 lines
991 B
Python
37 lines
991 B
Python
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import numpy as np
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import pandas as pd
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import tensorflow as tf
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from tensorflow.keras import layers
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def onezero(label):
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return 0 if label == 'unstable' else 1
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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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Y_train = X_train.pop('stabf')
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Y_test = X_test.pop('stabf')
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Y_train_one_zero = [onezero(x) for x in Y_train]
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Y_train_onehot = np.eye(2)[Y_train_one_zero]
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Y_test_one_zero = [onezero(x) for x in Y_test]
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Y_test_onehot = np.eye(2)[Y_test_one_zero]
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model = tf.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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model.compile(
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loss=tf.losses.BinaryCrossentropy(),
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optimizer=tf.optimizers.Adam(),
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metrics=[tf.keras.metrics.BinaryAccuracy()])
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history = model.fit(tf.convert_to_tensor(X_train, np.float32),
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Y_train_onehot, epochs=5)
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model.save('grid_stability.h5')
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