Ant-Based Data Reduction Algorithm for Classification
Prof. Svapnil Vakharia
, Prof. Mansi Shah , Kajal Mengar
Ant Colony Optimization (ACO), Data Mining,Classification, Data Reduction, Instance Selection.
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.
"Ant-Based Data Reduction Algorithm for Classification", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 2, page no.68 - 72, Feb-2016, Available :https://ijsdr.org/papers/IJSDR1602012.pdf
Volume 1
Issue 2,
February-2016
Pages : 68 - 72
Paper Reg. ID: IJSDR_160018
Published Paper Id: IJSDR1602012
Downloads: 000347043
Research Area: Engineering
Country: Ahmedabd, Gujarat, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
