A Novel Sentimental Analysis using Optimized Relevance Vector Machine Classifier

  • Authors

    • N. Saranya
    • R. Gunavathi
    • . .
    2018-09-27
    https://doi.org/10.14419/ijet.v7i4.7.20536
  • Optimization, Vector Machine Classifier, Cuckoo Search Optimization

  • Abstract

    Sentimental analysis is the process of identifying the human’s thoughts or feelings. So Many methods have been developed for the sentimental analysis. Machine learning is one of the widely used approaches towards sentiment classification. In this work, Sentimental analysis is done by using Relevance Vector Machine Classifier with Cuckoo Search Optimization. Here Relevance Vector Machine Classifier (RVMC) is combined with Cuckoo Search Optimization (CSO) for better accuracy and performance. Experiment is made with movie and twitter datasets. Accuracy, precision and recall of all other techniques are evaluated. Here the comparison is made among other algorithms. The result shows that RVMC-CSO algorithm gives accuracy and good performance than other algorithm like SVM, ELM and RVM.

     

     

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  • How to Cite

    Saranya, N., Gunavathi, R., & ., . (2018). A Novel Sentimental Analysis using Optimized Relevance Vector Machine Classifier. International Journal of Engineering & Technology, 7(4.7), 164-166. https://doi.org/10.14419/ijet.v7i4.7.20536

    Received date: 2018-09-29

    Accepted date: 2018-09-29

    Published date: 2018-09-27