ML-tutorial/logreg.py at master · aprameyabharadwaj/ML-tutorial · GitHub

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import numpy as np
import matplotlib.pyplot as plt
import pandas as pd


dataset = pd.read_csv('Social_Network_Ads.csv')
X = dataset.iloc[:, 2:4].values
y = dataset.iloc[:, 4].values

from sklearn.cross_validation import train_test_split
X_train , X_test , y_train , y_test = train_test_split(X , y , test_size = 0.25 , random_state = 0)


from sklearn.preprocessing import StandardScaler
sc_X = StandardScaler()
X_train = sc_X.fit_transform(X_train)
X_test = sc_X.transform(X_test)

from sklearn.linear_model import LogisticRegression
classifier  = LogisticRegression(random_state = 0)
classifier.fit(X_train,y_train)


y_pred = classifier.predict(X_test)


from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test , y_pred)


from matplotlib.colors import ListedColorMap
X_set , y_set = X_train , y_train
X1, X2 = np.meshgrid(np.arange())