!pip install jovian --upgrade --quiet

import pandas as pd
import pdb
msg=pd.read_csv('/content/naivetext1.csv',names=['message','label']) #names-> name of the cols
msg['labelnum']=msg.label.map({'pos':1,'neg':0})
X=msg.message
Y=msg.labelnum

from sklearn.model_selection import train_test_split
xtrain,xtest,ytrain,ytest=train_test_split(X,Y)

from sklearn.feature_extraction.text import CountVectorizer
count_vect = CountVectorizer()

xtrain_dtm = count_vect.fit_transform(xtrain)
xtest_dtm=count_vect.transform(xtest)

df=pd.DataFrame(xtrain_dtm.toarray(),columns=count_vect.get_feature_names())

from sklearn.naive_bayes import MultinomialNB
clf = MultinomialNB().fit(xtrain_dtm,ytrain)
predicted = clf.predict(xtest_dtm)

from sklearn import metrics
print('Accuracy metrics')
print('Accuracy of the classifer is',metrics.accuracy_score(ytest,predicted))
print('Confusion matrix')
print(metrics.confusion_matrix(ytest,predicted))
print('Recall and Precison ')
print(metrics.recall_score(ytest,predicted))
print(metrics.precision_score(ytest,predicted))

jovian.commit("ml-lab-program-4")