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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
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| Paper Title: | IMPROVEMENT OF CLASS IMBALANCE LEARNING TECHNIQUES USING UNSUPERVISED LEARNING APPROACHES |
| Authors Name: | Mr.R.Bulli Babu , Dr.Mohammed Ali Hussain |
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IJRTI_170160
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| Published Paper Id: | IJRTI1704043 |
| Published In: | Volume 2 Issue 4, April-2017 |
| DOI: | |
| Abstract: | Fraud is a hugely costly criminal activity which occurs in a number of domains. Data mining has been applied to fraud detection in both a supervised and non-supervised manner. When a supervised data mining approach is used, one of the biggest problems that are encountered, is the problem of class imbalance. The class imbalance problem is not unique to the domain of fraud, but also occurs in fields as diverse as medical diagnosis and quality control. There are two basic means of overcoming the class imbalance problem; these are data methods and algorithmic methods. Data methods generally involve an under sampling, over sampling or hybrid over/under sampling approach. Other data method investigated include SMOTE, which uses a K-NN learner to artificially synthesize minority class samples. Algorithmic methods investigated include using either a mis-classification cost in the case of the Meta cost procedure or Meta cost thresholds. Other algorithmic methods include the use of learners which are not sensitive to the class imbalance problem. The different methods for overcoming the class imbalance problem are implemented using open-source software. 3 datasets are used to investigate the usefulness of the different methods. 2 of the datasets are from the domain of fraud, while the third is from the domain of medical diagnosis. |
| Keywords: | Dataset, class imbalance, under-sampling, over-sampling, Class Imbalance Learning |
| Cite Article: | "IMPROVEMENT OF CLASS IMBALANCE LEARNING TECHNIQUES USING UNSUPERVISED LEARNING APPROACHES", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 4, page no.174 - 182, April-2017, Available :http://www.ijrti.org/papers/IJRTI1704043.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI1704043
Registration ID:170160
Published In: Volume 2 Issue 4, April-2017
DOI (Digital Object Identifier):
Page No: 174 - 182 Country: GUNTUR, ANDHRAPRADESH, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI1704043 Published Paper PDF: https://www.ijrti.org/papers/IJRTI1704043 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
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