Naivy Bay’s Classification Demo 2

Naivy Bay’s Classification Demo 2

 

import numpy as np

import matplotlib.pyplot as plt

import pandas as pd

import sklearn

 

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

X = dataset.iloc[:, [1, 2, 3]].values

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

X

y

 

from sklearn.preprocessing import LabelEncoder

le = LabelEncoder()

X[:,0] = le.fit_transform(X[:,0])

X

 

from sklearn.model_selection import train_test_split

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state = 0)

 

from sklearn.preprocessing import StandardScaler

sc = StandardScaler()

X_train = sc.fit_transform(X_train)

X_test = sc.transform(X_test)

X_train

 

from sklearn.naive_bayes import GaussianNB

classifier = GaussianNB()

classifier.fit(X_train, y_train)

 

y_pred  =  classifier.predict(X_test)

y_pred

 

y_test

 

# Making the Confusion Matrix

from sklearn.metrics import confusion_matrix, accuracy_score

ac = accuracy_score(y_test,y_pred)

cm = confusion_matrix(y_test, y_pred)

ac

 

cm