17 lines
673 B
Python
17 lines
673 B
Python
from models import create_model
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from rank import calculate_mean_and_sort_list, get_ranks, calculate_mape
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from data import load
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from sklearn.model_selection import train_test_split
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if __name__ == '__main__':
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X, y, names = load('WindData.csv')
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linear = create_model(X, y)
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ranks = get_ranks(linear, names)
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print("MEAN", calculate_mean_and_sort_list(ranks))
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for test_size in [0.001, 0.01, 0.05, 0.11]:
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X_train, X_test, Y_train, Y_test = train_test_split(X, y, test_size=test_size, random_state=100)
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mape = calculate_mape(X_train, X_test, Y_train, Y_test)
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print(f'MAPE for test_size={test_size} is {float("{:.3f}".format(mape))}')
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