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IUM_2.py
42
IUM_2.py
@ -3,38 +3,36 @@ from sklearn.model_selection import train_test_split
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from sklearn.preprocessing import StandardScaler
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def split(data):
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meteorite_train, meteorite_test = train_test_split(data, test_size=0.2, random_state=1)
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meteorite_train, meteorite_val = train_test_split(meteorite_train, test_size=0.25, random_state=1)
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return meteorite_train, meteorite_test, meteorite_val
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forest_train, forest_test = train_test_split(data, test_size=0.2, random_state=1)
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forest_train, forest_val = train_test_split(forest_train, test_size=0.25, random_state=1)
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return forest_train, forest_test, forest_val
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def normalization(data):
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scaler = StandardScaler()
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data['mass'] = scaler.fit_transform(data[['mass']])
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columns_to_normalize = data.columns[~data.columns.str.startswith('Soil_Type')]
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columns_to_normalize = columns_to_normalize.to_list()
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columns_to_normalize.remove('Cover_Type')
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data[columns_to_normalize] = scaler.fit_transform(data[columns_to_normalize])
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return data
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def preprocessing(data):
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data = data.dropna(subset=['reclat'])
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incorrect_years_index = data.loc[(data['year'] > 2016) | (data['year'] < 860)].index
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incorrect_location_index = data.loc[(data['reclat'] == 0) & (data['reclong'] == 0)].index
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data.drop(incorrect_years_index.union(incorrect_location_index), inplace=True)
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data.loc[(data['mass'].isnull()) & (data['name'].str.startswith('Österplana')), 'mass'] = 0
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#shuffle
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data = data.sample(frac = 1)
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return data
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data = pd.read_csv("meteorite-landings.csv")
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meteorite_train, meteorite_test, meteorite_val = split(data)
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data = pd.read_csv("covtype.csv")
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forest_train, forest_test, forest_val = split(data)
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meteorite_train = normalization(meteorite_train)
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meteorite_test = normalization(meteorite_test)
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meteorite_val = normalization(meteorite_val)
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forest_train = preprocessing(forest_train)
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forest_test = preprocessing(forest_test)
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forest_val = preprocessing(forest_val)
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meteorite_train = normalization(meteorite_train)
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meteorite_test = normalization(meteorite_test)
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meteorite_val = normalization(meteorite_val)
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forest_train = normalization(forest_train)
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forest_test = normalization(forest_test)
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forest_val = normalization(forest_val)
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meteorite_train.to_csv('meteorite_train.csv', encoding='utf-8')
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meteorite_test.to_csv('meteorite_test.csv', encoding='utf-8')
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meteorite_val.to_csv('meteorite_val.csv', encoding='utf-8')
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forest_train.to_csv('forest_train.csv', encoding='utf-8', index=False)
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forest_test.to_csv('forest_test.csv', encoding='utf-8', index=False)
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forest_val.to_csv('forest_val.csv', encoding='utf-8', index=False)
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