19 lines
575 B
Python
19 lines
575 B
Python
import pandas as pd
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import tensorflow as tf
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from sklearn.preprocessing import MinMaxScaler
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model = tf.keras.models.load_model('model.h5')
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data = pd.read_csv('data.csv', sep=';')
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data = pd.get_dummies(data, columns=['Sex', 'Medal'])
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data = data.drop(columns=['Name', 'Team', 'NOC', 'Games', 'Year', 'Season', 'City', 'Sport', 'Event'])
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scaler = MinMaxScaler()
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data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)
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X_test = data.filter(regex='Sex|Age')
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predictions = model.predict(X_test)
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pd.DataFrame(predictions).to_csv('predictions.csv', index=False) |