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Dynamic base classifier pool for classifier selection in Multiple Classifier Systems
2011 International Conference on Machine Learning and Cybernetics, 2011Multiple Classifier Systems (MCSs) are a method combining decisions of base classifiers. The set of the base classifiers is fixed in traditional MCSs. When applying MCSs in online learning environment, the base classifiers have to be updated frequently to adapt the change of the environment.
Patrick P. K. Chan +3 more
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CCC: Classifier Combination via Classifier
2011The combination of classifier has long been proposed as a method to improve the accuracy achieved in isolation by a single classifier. Most of the extant works focus on how to generate a group of "good" base classifiers, such as AdaBoost and Bagging. We are interested in the method of combining multiple classifiers.
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2000
Abstract Noun classifiers occur with a noun independently of any other element within a noun phrase or a clause. They categorize the entity in terms of the generic type or class it belongs to. Noun classifiers can be independent words, as in Mayan, Australian, and some Austronesian and Amazonian languages, or they can be affixes to nouns
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Abstract Noun classifiers occur with a noun independently of any other element within a noun phrase or a clause. They categorize the entity in terms of the generic type or class it belongs to. Noun classifiers can be independent words, as in Mayan, Australian, and some Austronesian and Amazonian languages, or they can be affixes to nouns
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Using machine learning Meta-Classifiers to detect financial frauds
Finance Research Letters, 2022Muhammad Atif Khan Achakzai, Peng Juan
exaly
k-Nearest Neighbour Classifiers - A Tutorial
ACM Computing Surveys, 2022Pádraig Cunningham, Sarah Jane Delany
exaly
Discrete Bayesian Network Classifiers
ACM Computing Surveys, 2014Concha Bielza, Pedro Larranaga
exaly
To classify or not to classify: That is the question
Behavioral and Brain Sciences, 1990openaire +1 more source