#emails-KNN

import pandas as pd

df=pd.read_csv('emails.csv')
print(df)

df.isnull().sum()

from sklearn.model_selection import train_test_split
X=df.drop('Prediction',axis=1)
y=df['Prediction']
X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2)

from sklearn.neighbors import KNeighborsClassifier
knn=KNeighborsClassifier()
knn.fit(X_train,y_train)
y_pred_knn=knn.predict(X_test)
y_pred_knn

from sklearn.metrics import confusion_matrix,classification_report
print("KNN Confusion matrix:\n",confusion_matrix(y_test,y_pred_knn))
print("\n\nKNN Classification report: \n",classification_report(y_test,y_pred_knn))


from sklearn.svm import SVC
svm=SVC(kernel='linear',probability=True)
svm.fit(X_train,y_train)
y_pred_svm=svm.predict(X_test)
y_pred_svm

print("SVM Confusion Matrix:\n", confusion_matrix(y_test,y_pred_svm))
print("SVM Classification report: \n",classification_report(y_test,y_pred_svm))