Literature DB >> 16724593

Improving multiclass pattern recognition by the combination of two strategies.

Nicolás García-Pedrajas1, Domingo Ortiz-Boyer.   

Abstract

We present a new method of multiclass classification based on the combination of one-vs-all method and a modification of one-vs-one method. This combination of one-vs-all and one-vs-one methods proposed enforces the strength of both methods. A study of the behavior of the two methods identifies some of the sources of their failure. The performance of a classifier can be improved if the two methods are combined in one, in such a way that the main sources of their failure are partially avoided.

Mesh:

Year:  2006        PMID: 16724593     DOI: 10.1109/TPAMI.2006.123

Source DB:  PubMed          Journal:  IEEE Trans Pattern Anal Mach Intell        ISSN: 0098-5589            Impact factor:   6.226


  2 in total

1.  Learning ECOC Code Matrix for Multiclass Classification with Application to Glaucoma Diagnosis.

Authors:  Xiaolong Bai; Swamidoss Issac Niwas; Weisi Lin; Bing-Feng Ju; Chee Keong Kwoh; Lipo Wang; Chelvin C Sng; Maria C Aquino; Paul T K Chew
Journal:  J Med Syst       Date:  2016-01-21       Impact factor: 4.460

2.  Experimental Study and Comparison of Imbalance Ensemble Classifiers with Dynamic Selection Strategy.

Authors:  Dongxue Zhao; Xin Wang; Yashuang Mu; Lidong Wang
Journal:  Entropy (Basel)       Date:  2021-06-28       Impact factor: 2.524

  2 in total

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