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A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles
March 2013 (vol. 25 no. 3)
pp. 494-501
| ASCII Text | x | ||
| Ludmila I. Kuncheva, "A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles," IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 3, pp. 494-501, March, 2013. | |||
| BibTex | x | ||
| @article{ 10.1109/TKDE.2011.234, author = {Ludmila I. Kuncheva}, title = {A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {25}, number = {3}, issn = {1041-4347}, year = {2013}, pages = {494-501}, doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.234}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Knowledge and Data Engineering TI - A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles IS - 3 SN - 1041-4347 SP494 EP501 EPD - 494-501 A1 - Ludmila I. Kuncheva, PY - 2013 KW - Classificagtion KW - Diversity methods KW - Image color analysis KW - Decision trees KW - Mathematical model KW - Feature extraction KW - Kappa-error diagrams KW - limits KW - Classifier ensembles KW - kappa-error diagrams KW - ensemble diversity VL - 25 JA - IEEE Transactions on Knowledge and Data Engineering ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2011.234
Kappa-error diagrams are used to gain insights about why an ensemble method is better than another on a given data set. A point on the diagram corresponds to a pair of classifiers. The x-axis is the pairwise diversity (kappa), and the y-axis is the averaged individual error. In this study, kappa is calculated from the 2\times2 correct/wrong contingency matrix. We derive a lower bound on kappa which determines the feasible part of the kappa-error diagram. Simulations and experiments with real data show that there is unoccupied feasible space on the diagram corresponding to (hypothetical) better ensembles, and that individual accuracy is the leading factor in improving the ensemble accuracy.
Index Terms:
Classificagtion,Diversity methods,Image color analysis,Decision trees,Mathematical model,Feature extraction,Kappa-error diagrams,limits,Classifier ensembles,kappa-error diagrams,ensemble diversity
Citation:
Ludmila I. Kuncheva, "A Bound on Kappa-Error Diagrams for Analysis of Classifier Ensembles," IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 3, pp. 494-501, March 2013, doi:10.1109/TKDE.2011.234
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