Gain ratio feed forward neural network algorithm to improve classification accuracy

  • Authors

    • Helen Josephine V. L
    • S. Duraisamy
    https://doi.org/10.14419/ijet.v7i4.21737

  • In the field of information technology, there is revolution that has led to an abundance of information in every field through Internet. The rapid growth in the mobile devices indicates that the users and industry are getting more at ease with the mobile environment. An incredible amount of mobile learning systems and users’ opinion about these apps are available in the form of reviews on the websites or in the social blogs or feedback. To classify these opinions, Neural Networks algorithm is mostly used to obtain high accuracy. To mine mobile learning app reviews, Gain Ratio based neural network algorithm for opinion mining system is proposed in this research paper. The main focus is to extract the polarity of the reviews, opinion it and conclude whether these reviews are positive or negative or neutral. This research work consists of four steps (i) Estimate score of the words in the review document by using Singular Value Decomposition (SVD) (ii) Feed forward the top ranked words with its weights from the input layer to hidden layer (iii) Calculate gain ratio and select top five positive and negative attributes (iv) Pass the selected attributes from input layer to output layer. This customized neural network classification algorithm helps to improve the classification accuracy.

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    V. L, H. J., & Duraisamy, S. (2018). Gain ratio feed forward neural network algorithm to improve classification accuracy. International Journal of Engineering & Technology, 7(4), 3579-3582. https://doi.org/10.14419/ijet.v7i4.21737