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python
3 years ago
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import pandas as pd import numpy as np from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression df = pd.read_csv('HIGGS.csv', header=None) df.head() df.shape df.describe() df = df.sample(n=1000000) df.head() X = df.iloc[:, 1:] Y = df.iloc[:, 0] X.head() Y.head() X_train, X_test = train_test_split(X, test_size=0.1) Y_train, Y_test = train_test_split(Y, test_size=0.1) print(X_train.shape, X_test.shape, Y_train.shape, Y_test.shape) logisticRegr = LogisticRegression() logisticRegr.fit(X_train, Y_train) predictions = logisticRegr.predict(X_test) score = logisticRegr.score(X_test, Y_test) print(score)
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