/*
Program to implement the SVM For Spam Mail Detection..
Developed by: PRASANNA R
RegisterNumber: 212222040120

import chardet 
file='spam.csv'
with open(file, 'rb') as rawdata: 
    result = chardet.detect(rawdata.read(100000))
result
import pandas as pd
data = pd.read_csv("spam.csv",encoding="Windows-1252")
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
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)
print("Y_prediction Value: ",Y_pred)

from sklearn import metrics
accuracy=metrics.accuracy_score(Y_test,Y_pred)
accuracy
*/