Attribute related methods for improvement of ID3 Algorithm in classification of data: A review

Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the...

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Main Authors: Nur Farahaina, Idris, Mohd Arfian, Ismail
Format: Article
Language:English
Published: Peerj Inc. 2020
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/31461/
http://umpir.ump.edu.my/id/eprint/31461/1/attribute-related-methods-for-improvement-of-id3-algorithm-in-classification-of-data-a-review-5f75ea3618a5a.pdf
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author Nur Farahaina, Idris
Mohd Arfian, Ismail
author_facet Nur Farahaina, Idris
Mohd Arfian, Ismail
author_sort Nur Farahaina, Idris
building UMP Institutional Repository
collection Online Access
description Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. The use of information gain in the ID3 algorithm as the attribute selection criteria is not to assess the relationship between classification and the dataset’s attributes. The objective of the study being conducted is to implement the attribute related methods to solve the shortcomings of the ID3 algorithm like the tendency to select attributes with many values and also improve the performance of ID3 algorithm. The techniques of attribute related methods studied in this paper were mutual information, association function and attribute weighted. All the techniques assist the decision tree to find the most optimal attributes in each generation of the tree. Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. All of the reviewed techniques have their advantages and disadvantages and useful to solve the classification problems. Implementation of the techniques with ID3 algorithm is being discussed thoroughly.
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spelling ump-314612021-06-20T09:37:27Z http://umpir.ump.edu.my/id/eprint/31461/ Attribute related methods for improvement of ID3 Algorithm in classification of data: A review Nur Farahaina, Idris Mohd Arfian, Ismail QA75 Electronic computers. Computer science Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. Nevertheless, there are some limitations in ID3 algorithm that can affect the performance in the classification of data. The use of information gain in the ID3 algorithm as the attribute selection criteria is not to assess the relationship between classification and the dataset’s attributes. The objective of the study being conducted is to implement the attribute related methods to solve the shortcomings of the ID3 algorithm like the tendency to select attributes with many values and also improve the performance of ID3 algorithm. The techniques of attribute related methods studied in this paper were mutual information, association function and attribute weighted. All the techniques assist the decision tree to find the most optimal attributes in each generation of the tree. Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. All of the reviewed techniques have their advantages and disadvantages and useful to solve the classification problems. Implementation of the techniques with ID3 algorithm is being discussed thoroughly. Peerj Inc. 2020 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/31461/1/attribute-related-methods-for-improvement-of-id3-algorithm-in-classification-of-data-a-review-5f75ea3618a5a.pdf Nur Farahaina, Idris and Mohd Arfian, Ismail (2020) Attribute related methods for improvement of ID3 Algorithm in classification of data: A review. Technology Reports of Kansai University, 62 (8). pp. 4759-4767. ISSN 04532198. (Published) https://www.kansaiuniversityreports.com/ TRKU-04-09-2020-11072
spellingShingle QA75 Electronic computers. Computer science
Nur Farahaina, Idris
Mohd Arfian, Ismail
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title_full Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title_fullStr Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title_full_unstemmed Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title_short Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
title_sort attribute related methods for improvement of id3 algorithm in classification of data: a review
topic QA75 Electronic computers. Computer science
url http://umpir.ump.edu.my/id/eprint/31461/
http://umpir.ump.edu.my/id/eprint/31461/
http://umpir.ump.edu.my/id/eprint/31461/
http://umpir.ump.edu.my/id/eprint/31461/1/attribute-related-methods-for-improvement-of-id3-algorithm-in-classification-of-data-a-review-5f75ea3618a5a.pdf