International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 6  (June 2017), Pages:  96-103


Title: A review on comparative performance analysis of associative classifiers

Author(s):  Zulfiqar Ali 1, 2, * , Waseem Shahzad 1, Syed Khuram Shahzad 2

Affiliation(s):

1Department of Computer Science, National University of Computer & Emerging Science, Islamabad, Pakistan
2Department of Computer Science and Information Technology, The University of Lahore, Lahore, Pakistan

https://doi.org/10.21833/ijaas.2017.06.014

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Abstract:

In this study we provided comparative study of associative classifiers which can be exploited for the discovery of business rules from the huge structured and unstructured data that can be used in the business analytic. Associative classification is a hybrid approach combining the classification rules mining and association rules mining that are two important data mining tasks. There are various emerging classification problems in various domains of knowledge like medical data, images, audio, video and textual data. Associative Classification approaches are exploited in various fields for the classification purposes. We compare the selective associative classification methods namely CBA, CBA2, CMAR-C, CFAR-C, CPAR-C, and Fuzzy-FARCHD-C by exploiting the implementation of these methods in KEEL data mining tool on public datasets. Our experimental results reveals that the performance of the Fuzzy-FARCHD-C is promising than other methods in terms of accuracy. The performance of the associative classifiers drastically decreases on the datasets with higher number classes and attributes. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Associative classification, Association rule mining, KEEL, Data mining

Article History: Received 26 December 2016, Received in revised form 10 March 2017, Accepted 15 April 2017

Digital Object Identifier: 

https://doi.org/10.21833/ijaas.2017.06.014

Citation:

Ali Z, Shahzad W, and Shahzad SK (2017). A review on comparative performance analysis of associative classifiers. International Journal of Advanced and Applied Sciences, 4(6): 96-103

http://www.science-gate.com/IJAAS/V4I6/Ali.html


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