mkumar262006 / implementation-of-svm-for-spam-mail-detection

Implementation-of-SVM-For-Spam-Mail-Detection

AIM:

To write a program to implement the SVM For Spam Mail Detection.

Equipments Required:

1. Hardware – PCs
2. Anaconda – Python 3.7 Installation / Jupyter notebook

Algorithm:

STEP 1 : Start STEP 2 : Preprocessing the data STEP 3 : Feature Extraction STEP 4 : Training the SVM model STEP 5 : Model Evalutaion STEP 6 : Stop

Program:

/*
Program to implement the SVM For Spam Mail Detection..
Developed by: MANOJ KUMAR S
RegisterNumber: 212223240082
*/

import pandas as pd
data=pd.read_csv("C:/Users/admin/Downloads/spam.csv",encoding = 'Windows-1252')
from sklearn.model_selection import train_test_split

data

Output:

data.shape

Output:

x=data["v2"].values

y=data["v1"].values

x.shape

Output:

y.shape

Output:

x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.2,random_state=0)

x_train

Output:

x_train.shape

Output:

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)

Output:

y_pred=svc.predict(x_test)
y_pred

Output:

from sklearn.metrics import accuracy_score,confusion_matrix,classification_report

acc=accuracy_score(y_test,y_pred)
acc

Output:

con=confusion_matrix(y_test,y_pred)
print(con)

Output:

cl=classification_report(y_test,y_pred)
print(cl)

Output:

Result:

Thus the program to implement the SVM For Spam Mail Detection is written and verified using python programming.