This paper presents a method for combining classifiers that uses estimates of each individual classifier's local accuracy in small regions of feature space ...
This paper presents a method for combining classifiers that use estimates of each individual classifier's local accuracy in small regions of feature space ...
THERE are two basic approaches a Combination of Multiple Classi- fiers (CMC) algorithm may take: classifier fusion and dynamic classifier selection.
This paper presents a method for combining classifiers that uses estimates of each individual classifier's local accuracy in small regions of feature space ...
A method for combining classifiers that use estimates of each individual classifier's local accuracy in small regions of feature space surrounding an ...
This paper presents a method for combining classifiers that uses estimates of each individual classifier's local accuracy in small regions of feature space ...
Apr 27, 2021 · The basic idea is to estimate each classifier's accuracy in local region of feature space surrounding an unknown test sample, and then use the ...
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How do you combine classifiers?
What is a combination of classifiers in pattern recognition?
Combination of multiple classifiers using local accuracy estimates. Pattern Analysis and Machine Intel- ligence, IEEE Transactions on, 19(4):405–410, 1997 ...
This paper proposes a novel algorithm for multiple classifiers combination based on clustering and selection technique (called M3CS)
Classifier combination methods have proved to be an effective tool to increase the performance of pattern recognition applications.