Detecting Credit Card Fraud using Data Mining Techniques - Meta-Learning

T  Abdul Razak   and G  Najeeb Ahmed

doi:10.17485/ijst/2015/v8i28/83326

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Detecting Credit Card Fraud using Data Mining Techniques - Meta-Learning

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i28/83326

Year: 2015, Volume: 8, Issue: 28, Pages: 1-9

Original Article

Detecting Credit Card Fraud using Data Mining Techniques - Meta-Learning

T. Abdul Razak^1* and G. Najeeb Ahmed²

¹Research Department of Computer Science, Jamal Mohammed College, Tiruchirapalli - 620 024, Tamil Nadu, India; [email protected]
² Research and Development, Bharathiar University, Coimbatore - 641046, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Data mining and machine learning techniques help us to better and deeper understanding of collected data. Meta-learning techniques extend this concept by providing methods for knowledge discovery process automatization. Meta-learning introduces various interesting concepts, including data meta-features, meta-knowledge, algorithm recommendation systems, autonomous process builders, etc. All these techniques aim to improve usually expensive and demanding data mining analysis. This paper focus on general overview of basic data mining, machine learning and meta-learning techniques, while focusing on state-of-the-art, basic formalisms and principles, interesting applications and possible future development in the field of meta-learning.
Keywords: Data Mining, DMA, KDD, Machine Learning, Meta-Learning