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Classification Through Machine Learning Technique: C4.5 Algorithm based on Various Entropies

by Seema Sharma, Jitendra Agrawal, Sanjeev Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 16
Year of Publication: 2013
Authors: Seema Sharma, Jitendra Agrawal, Sanjeev Sharma
10.5120/14249-2444

Seema Sharma, Jitendra Agrawal, Sanjeev Sharma . Classification Through Machine Learning Technique: C4.5 Algorithm based on Various Entropies. International Journal of Computer Applications. 82, 16 ( November 2013), 28-32. DOI=10.5120/14249-2444

@article{ 10.5120/14249-2444,
author = { Seema Sharma, Jitendra Agrawal, Sanjeev Sharma },
title = { Classification Through Machine Learning Technique: C4.5 Algorithm based on Various Entropies },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 16 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 28-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number16/14249-2444/ },
doi = { 10.5120/14249-2444 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:57:55.475425+05:30
%A Seema Sharma
%A Jitendra Agrawal
%A Sanjeev Sharma
%T Classification Through Machine Learning Technique: C4.5 Algorithm based on Various Entropies
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 16
%P 28-32
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is an interdisciplinary field of computer science and is referred to extracting or mining knowledge from large amounts of data. Classification is one of the data mining techniques that maps the data into the predefined classes and groups. It is used to predict group membership for data instances. There are many areas that adapt Data mining techniques such as medical, marketing, telecommunications, and stock, health care and so on. The C4. 5 can be referred as the statistic Classifier. This algorithm uses gain radio for feature selection and to construct the decision tree. It handles both continuous and discrete features. C4. 5 algorithm is widely used because of its quick classification and high precision. This paper proposed a C4. 5 classifier based on the various entropies (Shannon Entropy, Havrda and Charvt entropy, Quadratic entropy) instance of Shannon entropy for classification. Experiment results show that the various entropy based approach is effective in achieving a high classification rate.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Classification technique Machine learning Decision tree technique C4. 5 algorithm.

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