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An Algorithm to Construct Decision Tree for Machine Learning based on Similarity Factor

by Neha Patel, Divakar Singh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 111 - Number 10
Year of Publication: 2015
Authors: Neha Patel, Divakar Singh
10.5120/19575-1376

Neha Patel, Divakar Singh . An Algorithm to Construct Decision Tree for Machine Learning based on Similarity Factor. International Journal of Computer Applications. 111, 10 ( February 2015), 22-26. DOI=10.5120/19575-1376

@article{ 10.5120/19575-1376,
author = { Neha Patel, Divakar Singh },
title = { An Algorithm to Construct Decision Tree for Machine Learning based on Similarity Factor },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 111 },
number = { 10 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 22-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume111/number10/19575-1376/ },
doi = { 10.5120/19575-1376 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:47:32.000745+05:30
%A Neha Patel
%A Divakar Singh
%T An Algorithm to Construct Decision Tree for Machine Learning based on Similarity Factor
%J International Journal of Computer Applications
%@ 0975-8887
%V 111
%N 10
%P 22-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is one of the most important steps of the knowledge discovery in databases process and is considered as significant subfield in knowledge management. A classification of the data mining methods would greatly simplify the understanding of the whole space of available methods. Decision tree learning algorithm has been successfully used in expert systems in capturing knowledge. Most decision tree classifiers are designed to classify the data with categorical or Boolean class labels. To the best of our knowledge, no previous research has considered the induction of decision trees from data with data dissimilarities. This work proposes a novel classification algorithm for learning decision tree classifiers from data using dissimilarities with less complexity and less time to construct decision tree.

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Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Classification Decision Tree ID3 Algorithm.

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