Pothina Praveena
GITAM Deemed to be University

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Evolution of hybrid distance based kNN classification N. Suresh Kumar; Pothina Praveena
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i2.pp510-518

Abstract

The evolution of classification of opinion mining and user review analysis span from decades reaching into ubiquitous computing in efforts such as movie review analysis. The performance of linear and non-linear models are discussed to classify the positive and negative reviews of movie data sets. The effectiveness of linear and non-linear algorithms are tested and compared in-terms of average accuracy. The performance of various algorithms is tested by implementing them on internet movie data base (IMDB). The hybrid kNN model optimizes the performance classification interns of accuracy. The accuracy of polarity prediction rate is improved with random-distance-weighted-kNN-ABC when compared with kNN algorithm applied alone.