/*
Program to implement the SVM For Spam Mail Detection..
Developed by: Aakash S
RegisterNumber:  212221240001
*/
import pandas as pd
import matplotlib.pyplot as plt
data=pd.read_csv("spam.csv",encoding='latin-1')
data.head()
data.info()
data.isnull().sum()
x=data["v1"].values
y=data["v2"].values
from sklearn.model_selection import train_test_split
x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=0)
from sklearn.feature_extraction.text import CountVectorizer #CountVectorizer is a method to convert textt to neumerical data.the text is transformed to a sparse matrix
cv=CountVectorizer()
x_train=cv.fit_transform(x_train)
x_test=cv.transform(x_test)
from sklearn.svm import SVC
svc=SVC()
svc.fit(x_train,y_train)
y_pred = svc.predict(x_test)
y_pred
from sklearn import metrics
accuracy= metrics.accuracy_score(y_test,y_pred)
accuracy