ABSTRACT
For a very long time, making a machine understand the natural language and process it to perform a creative task has been a problem of high priority to human. Classifying whether a product being sold is worth buying makes it easier for the buyer to make his decision. This also helps the seller to analyse his sales. In this paper, we have done a comparative analysis of dierent machine learning algorithms and studied how well each algorithm works in classifying human sentiments from natural language in text based product reviews.
