Publication 2002 Issue No. 2 - February Abstract - A Theoretical Study on Six Classifier Fusion Strategies
A Theoretical Study on Six Classifier Fusion Strategies
February 2002 (vol. 24 no. 2)
pp. 281-286
 ASCII Text x Ludmila I. Kuncheva, "A Theoretical Study on Six Classifier Fusion Strategies," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 2, pp. 281-286, February, 2002.
 BibTex x @article{ 10.1109/34.982906,author = {Ludmila I. Kuncheva},title = {A Theoretical Study on Six Classifier Fusion Strategies},journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},volume = {24},number = {2},issn = {0162-8828},year = {2002},pages = {281-286},doi = {http://doi.ieeecomputersociety.org/10.1109/34.982906},publisher = {IEEE Computer Society},address = {Los Alamitos, CA, USA},}
 RefWorks Procite/RefMan/Endnote x TY - JOURJO - IEEE Transactions on Pattern Analysis and Machine IntelligenceTI - A Theoretical Study on Six Classifier Fusion StrategiesIS - 2SN - 0162-8828SP281EP286EPD - 281-286A1 - Ludmila I. Kuncheva, PY - 2002KW - Classifier combinationKW - theoretical errorKW - fusion methodsKW - order statisticsKW - majority voteKW - independent classifiers.VL - 24JA - IEEE Transactions on Pattern Analysis and Machine IntelligenceER -

Abstract—We look at a single point in the feature space, two classes, and $L$ classifiers estimating the posterior probability for class $\omega_1$. Assuming that the estimates are independent and identically distributed (normal or uniform), we give formulas for the classification error for the following fusion methods: average, minimum, maximum, median, majority vote, and oracle.

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Index Terms:
Classifier combination, theoretical error, fusion methods, order statistics, majority vote, independent classifiers.
Citation:
Ludmila I. Kuncheva, "A Theoretical Study on Six Classifier Fusion Strategies," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 2, pp. 281-286, Feb. 2002, doi:10.1109/34.982906