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- import matplotlib.pyplot as plt
- import pandas as pd
- dataset = pd.read_excel('C:data.xlsx')
- X = dataset.iloc[:, 56:112]
- y = dataset.iloc[:, 113]
- from sklearn.cross_validation import train_test_split
- X_train, X_test , y_train , y_test = train_test_split(X, y, test_size=0.2 ,
- random_state=42)
- from sklearn.preprocessing import StandardScaler
- sc = StandardScaler()
- X_train = sc.fit_transform(X_train)
- X_test = sc.transform(X_test)
- from sklearn.linear_model import LogisticRegression
- classifier = LogisticRegression(random_state=0)
- classifier.fit(X_train, y_train)
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