Classification Rules and Genetic Algorithm in Data Mining

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Classification Rules and Genetic Algorithm in Data Mining

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Abstract

Databases today are ranging in size into the Tera Bytes. It is an information extraction activity whose goal is to discover hidden facts contained in databases. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Major Data Mining Tasks and processes include

References

8 Cites in Article
  1. Gregory Piatetsky (2007). Data mining and knowledge discovery 1996 to 2005: overcoming the hype and moving from "university" to "business" and "analytics.
  2. Hans-Peter Kriegel,Karsten Borgwardt,Peer Kröger,Alexey Pryakhin,Matthias Schubert,Arthur Zimek (2007). Future trends in data mining.
  3. Qi Luo (2008). Advancing Knowledge Discovery and Data Mining" Knowledge Discovery and Data Mining.
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  6. Sufal Das,Banani Saha (2009). Data Quality Mining using Genetic Algorithm.
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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Mr. Puneet Chadha. 2012. "Classification Rules and Genetic Algorithm in Data Mining". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C15).

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-C Classification H.2.8
Version of record

v1.2

Issue date
December 11, 2012

Language
English
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Classification Rules and Genetic Algorithm in Data Mining

Mr. Chadha
Mr. Chadha Department of Computer Science, D.A.V. College, Sector-10, Affiliated to Panjab University, Chandigarh-160010