Sentimental Analysis using Twin Extreme Learning Machine Classifier
Journal Title: IMPACT : International Journal of Research in Humanities, Arts and Literature ( IMPACT : IJRHAL ) - Year 2018, Vol 6, Issue 9
Abstract
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral. It’s also known as opinion mining, deriving the opinion or attitude of a speaker. A common use case for this technology is to find out how people feel about a specific topic. Many methods and approaches were implemented for this sentiment analysis. This paper works with TELM for the better performance and accuracy of the sentimental analysis. Twin Extreme Learning Machines (TELM) are the extension of Extreme Learning Machines (ELM). This approach gives the good result when compared to other techniques. Here the comparison is made among TELM, ELM, SVM and TSVM also experiment shows that TELM has better accuracy than others.
Authors and Affiliations
N. Saran ya
Keywords
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