A Statistical approach to evaluate the efficiency and effectiveness of the Machine Learning algorithms analyzing Sentiments

Archana Praveen Kumar, Ashalatha Nayak, K. Manjula Shenoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the process of analyzing sentiments for a given dataset various machine learning techniques are used. The models using these learning algorithms help in determining the sentiments across the textual documents. There is a need to evaluate the effectiveness of the models in terms of analyzing and predicting sentiments. This paper provides a statistical approach to measure the effectiveness of the models and also evaluates their effectiveness with respect to the data representations. Here an experimental research is carried out with an inductive mode to measure and evaluate the models. The models are built using Decision Tree, Naive Bayes and Support Vector Machines. Data has been represented using features of Term Frequency and Inverse Document Frequency and Bag-of-words. Statistical tools used for measuring the models are Chi-square test and Analysis of Variance.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728137353
DOIs
Publication statusPublished - 08-2019
Event3rd IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Manipal, India
Duration: 11-08-201912-08-2019

Publication series

Name2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings

Conference

Conference3rd IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019
CountryIndia
CityManipal
Period11-08-1912-08-19

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Electrical and Electronic Engineering
  • Computational Mathematics
  • Control and Optimization

Cite this

Kumar, A. P., Nayak, A., & Shenoy, K. M. (2019). A Statistical approach to evaluate the efficiency and effectiveness of the Machine Learning algorithms analyzing Sentiments. In 2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings [9008028] (2019 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DISCOVER47552.2019.9008028