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Multi-label Classification with Multiple Label Correlation Orders And Structures

Electronic Theses of Indian Institute of Science

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Field Value
 
Title Multi-label Classification with Multiple Label Correlation Orders And Structures
 
Creator Posinasetty, Anusha
 
Subject Multi Label Classification
Multi Label Classification-Feature Selection Support Vector Machines (MC-FSSVM)
Structural Support Vector Machine
Multiple Label Correlation Orders and Structures
Machine Learning
Multiclass Classification
Multi-Label Classification Algorithms
Structural SVM
Computer Science
 
Description Multilabel classification has attracted much interest in recent times due to the wide applicability of the problem and the challenges involved in learning a classifier for multilabeled data. A crucial aspect of multilabel classification is to discover the structure and order of correlations among labels and their effect on the quality of the classifier. In this work, we propose a structural Support Vector Machine (structural SVM) based framework which enables us to systematically investigate the importance of label correlations in multi-label classification. The proposed framework is very flexible and provides a unified approach to handle multiple correlation orders and structures in an adaptive manner and helps to effectively assess the importance of label correlations in improving the generalization performance. We perform extensive empirical evaluation on several datasets from different domains and present results on various performance metrics. Our experiments provide for the first time, interesting insights into the following questions: a) Are label correlations always beneficial in multilabel classification? b) What effect do label correlations have on multiple performance metrics typically used in multilabel classification? c) Is label correlation order significant and if so, what would be the favorable correlation order for a given dataset and a given performance metric? and d) Can we make useful suggestions on the label correlation structure?
 
Contributor Shevade, Shirish
 
Date 2018-06-18T10:35:53Z
2018-06-18T10:35:53Z
2018-06-18
2016
 
Type Thesis
 
Identifier http://etd.iisc.ernet.in/2005/3719
http://etd.ncsi.iisc.ernet.in/abstracts/3541/G27793-Abs.pdf
 
Language en_US
 
Relation G27793