27 lines
661 B
Python
27 lines
661 B
Python
import pandas as pd
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import tensorflow
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from keras.applications.densenet import layers
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def main():
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train_data_x = pd.read_csv('./X_train.csv')
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adults_train = train_data_x.copy()
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adults_predict = train_data_x.pop('age')
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normalize = layers.Normalization()
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normalize.adapt(adults_train)
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adult_model = tensorflow.keras.Sequential([
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normalize,
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layers.Dense(64),
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layers.Dense(1)
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])
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adult_model.compile(
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loss=tensorflow.keras.losses.MeanSquaredError(),
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optimizer=tensorflow.keras.optimizers.Adam())
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adult_model.fit(adults_train, adults_predict, epochs=500)
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adult_model.save('model')
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