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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
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← Back to VOLUME 5, ISSUE 8, AUGUST 2016

A Review of Label Dependency and Feature Similarity for Multi-Label Classification

Rohit Tiwari, Shivank Kumar Soni

DOI: 10.17148/IJARCCE.2016.58127

Abstract: The increasing rate of data diversity in current decade faced a problem of data categorization. Data categorization used a classification technique such as KNN, decision tree and support vector machine. The process of classification divided into two sections one is trained model and other is test model. The assign class measured the similarity between trained and test. The dependency of feature bound the limitation of accuracy of classifier. The process of classification mapped data into labels and labels categorized in the different predefined class for the classification purpose. This paper concludes multi label classification technique removal of similarity of dependency.



Keywords: Multi-Class Classification, Label Dependency, Data Mining.

How to Cite:

[1] Rohit Tiwari, Shivank Kumar Soni, “A Review of Label Dependency and Feature Similarity for Multi-Label Classification,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2016.58127