Proposed Machine Learning Classifier Algorithm for Sentiment Analysis
Divyanshu Diwakar, Rajeev Kumar, Bhupesh Gour, Asif Khan · 2019
Text Mining has emerged as an active domain in the field of NLP (Natural Language Processing) and due to availability of large data sets of reviews, it has become easy to do sentiment analysis and extract the result from it, but Now-a-days the objectives are expressed in different ways making the data massive and difficult to understand for machines. In this research work, machines are first trained (Supervised learning) with the help of the predefined data (or more clearly reviews) and then tested with the reviews available. This Research work will show you the working of a system that uses the supervised training which classifies a product review as positive or negative using various classifier algorithms like KNN, Logistic Regression and Support Vector Machines. The model which will give the more accuracy will be considered as the best model.