# -*- coding: utf-8 -*-
"""
Created on Tue Nov  6 08:05:27 2018

@author: Nik
"""

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

dataset = pd.read_csv('Social_Network_Ads.csv')

X = dataset.iloc[:,2:4].values
y = dataset.iloc[:,-1].values

from sklearn.model_selection 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 = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)

from sklearn.decomposition import KernelPCA
pca = KernelPCA(n_components=2,kernel='rbf')
X_train = pca.fit_transform(X_train)
X_test = pca.transform(X_test)

from sklearn.linear_model import LogisticRegression
classifier = LogisticRegression()
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)
print(cm)
