Abhilasha Nakra

Work place: DCRUST Murthal/ECE, Sonipat, 131039, India

E-mail: abhilashanakra@gmail.com


Research Interests: Computational Learning Theory


Abhilasha Nakra received her M.Tech degree from DCRUST Murthal, Haryana in 2014 and is pursuing PhD in the department of Electronics & Communication from the same institute. Her major research interests include Signal Processing and Machine learning.

Author Articles
Comparative Analysis of Bayes Net Classifier, Naive Bayes Classifier and Combination of both Classifiers using WEKA

By Abhilasha Nakra Manoj Duhan

DOI: https://doi.org/10.5815/ijitcs.2019.03.04, Pub. Date: 8 Mar. 2019

Authors here tried to use the WEKA tool to evaluate the performance of various classifiers on a dataset to come out with the optimum classifier, for a particular application. A Classifier is an important part of any machine learning application. It is required to classify various classes and get to know whether the predicted class lies in the true class. There are various performance analysis measures to judge the efficiency of a classifier and there are many tools which provide oodles of classifiers. In the present investigation, Bayes Net, Naive Bayes and their combination have been implemented using WEKA. It has been concluded that the combination of Bayes Net and Naive Bayes provides the maximum classification efficiency out of these three classifiers. Such a hybridization approach will always motivate for combining different classifiers to get the best results.

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