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Review of Large-Scale Coordinate Descent Algorithms for Multi-class Classification with Memory Constraints

Jovanovich, Aleksandar
http://rave.ohiolink.edu/etdc/view?acc_num=ysu1369860195

Abstract Details

2013, Master of Computing and Information Systems, Youngstown State University, Department of Computer Science and Information Systems.
Big data can impact the performance of many standard measures used for classification. Specifically the efficiency of multi-class classification algorithms when the dataset is too large to fit into limited memory available needs to be explored. Different algorithms with varying complexity have been proposed in the literature. Two of the most recognized classification algorithms, batch learning and online learning have emerged as the most consistent options when solving for a multi-class problems. Presently a gap in the documentation of such algorithms exists in the literature available. Furthermore, the recent development of the online multi-class solver warrants a detailed examination. This thesis will address both concerns, providing detailed documentation of the analysis, comparisons of the algorithms, plots of the results, as well as a discussion about the findings.
Alina Lazar, PhD (Committee Chair)
Guang-Hwa Chang, PhD (Committee Member)
Perera Graciela, PhD (Committee Member)
51 p.
Computer Science; Information Science; Information Systems; Statistics
Classification; Multi-class Classification Large-Scale; Coordinate Descent; Memory Constraints

Recommended Citations

Citations

  • Jovanovich, A. (2013). Review of Large-Scale Coordinate Descent Algorithms for Multi-class Classification with Memory Constraints [Master's thesis, Youngstown State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1369860195

    APA Style (7th edition)

  • Jovanovich, Aleksandar. Review of Large-Scale Coordinate Descent Algorithms for Multi-class Classification with Memory Constraints. 2013. Youngstown State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ysu1369860195.

    MLA Style (8th edition)

  • Jovanovich, Aleksandar. "Review of Large-Scale Coordinate Descent Algorithms for Multi-class Classification with Memory Constraints." Master's thesis, Youngstown State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1369860195

    Chicago Manual of Style (17th edition)

ysu1369860195
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© 2013, all rights reserved.
This open access ETD is published by Youngstown State University and OhioLINK.