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- W2964297678 abstract "Classification involves the learning of the mapping function that associates input samples to corresponding target label. There are two major categories of classification problems: Single-label classification and Multi-label classification. Traditional binary and multi-class classifications are sub-categories of single-label classification. Several classifiers are developed for binary, multi-class and multi-label classification problems, but there are no classifiers available in the literature capable of performing all three types of classification. In this paper, a novel online universal classifier capable of performing all the three types of classification is proposed. Being a high speed online classifier, the proposed technique can be applied to streaming data applications. The performance of the developed classifier is evaluated using datasets from binary, multi-class and multi-label problems. The results obtained are compared with state-of-the-art techniques from each of the classification types." @default.
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- W2964297678 date "2016-10-01" @default.
- W2964297678 modified "2023-10-16" @default.
- W2964297678 title "An online universal classifier for binary, multi-class and multi-label classification" @default.
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- W2964297678 doi "https://doi.org/10.1109/smc.2016.7844809" @default.
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