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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: Ant-Based Data Reduction Algorithm for Classification
Authors Name: Prof. Svapnil Vakharia , Prof. Mansi Shah , Kajal Mengar
Unique Id: IJSDR1602012
Published In: Volume 1 Issue 2, February-2016
Abstract: Data reduction is the process of minimizing the amount of data that needs to be stored in a data storage environment. Data reduction can increase storage efficiency and reduce costs.It also decreases size of the training set presented to the algorithm by keeping only the most representative instances. In this paper, we introduce ADR-Miner with c4.5 and attribute selected classifier, novel data reduction algorithm that utilizes ant colony optimization (ACO). ADR-Miner is designed to perform instance selection to improve the predictive effectiveness of the constructed classification models. Empirical evaluations on 20 benchmark data sets with three well-known classification algorithms show that ADR-Miner improves the predictive quality of the produced classifiers.
Keywords: Ant Colony Optimization (ACO), Data Mining,Classification, Data Reduction, Instance Selection.
Cite Article: "Ant-Based Data Reduction Algorithm for Classification", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 2, page no.68 - 72, Feb-2016, Available :http://www.ijsdr.org/papers/IJSDR1602012.pdf
Downloads: 000102287
Publication Details: Published Paper ID: IJSDR1602012
Registration ID:160018
Published In: Volume 1 Issue 2, February-2016
DOI (Digital Object Identifier):
Page No: 68 - 72
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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