29 lines
873 B
Python
29 lines
873 B
Python
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.ensemble import RandomForestClassifier
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from sklearn.svm import SVR
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from sklearn import preprocessing
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from sklearn import utils
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data = pd.read_csv('starclusters-global-parameters2.dat',skiprows=1 ,delim_whitespace=True, header=None)
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shuffled_data = data.sample(frac=1, random_state=42)
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n = int(0.8 * len(shuffled_data))
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data_train = shuffled_data[:n]
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data_test = shuffled_data[n:]
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X_train = data_train.iloc[:, 1:-1].values
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y_train = data_train.iloc[:, -1].values
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lab = preprocessing.LabelEncoder()
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y_transformed = lab.fit_transform(y_train)
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X_test = data_test.iloc[:, 1:-1].values
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classifier = RandomForestClassifier()
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classifier.fit(X_train, y_transformed)
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y_pred = classifier.predict(X_test)
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data_test['8'] = list(y_pred)
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data_test.to_csv('prediction.dat', sep=' ', index=False)
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