  Sentiment analysis is a vast area in the Machine learning domain. A lot of
work is done on datasets and their analysis of the English Language. In
Pakistan, a huge amount of data is in roman Urdu language, it is scattered all
over the social sites including Twitter, YouTube, Facebook and similar
applications. In this study the focus domain of dataset gathering is YouTube
comments. The Dataset contains the comments of people over different Pakistani
dramas and TV shows. The Dataset contains multi-class classification that is
grouped The comments into positive, negative and neutral sentiment. In this
Study comparative analysis is done for five supervised learning Algorithms
including linear regression, SVM, KNN, Multi layer Perceptron and Na\"ive Bayes
classifier. Accuracy, recall, precision and F-measure are used for measuring
performance. Results show that accuracy of SVM is 64 percent, which is better
than the rest of the list.
