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- W2802904253 abstract "In most real life applications of classification, samples are imbalanced. Usually, this is due to the difficulty of data collection. Large margin, or instance based classifiers suffer a lot from sparsity of samples close to the dichotomy. In this work, we propose an improvement to a recent technique developed for rare class classification. The experimental results show a definite performance gain." @default.
- W2802904253 created "2018-05-17" @default.
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- W2802904253 date "2018-01-01" @default.
- W2802904253 modified "2023-09-23" @default.
- W2802904253 title "Improving the Performance of the k Rare Class Nearest Neighbor Classifier by the Ranking of Point Patterns" @default.
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- W2802904253 doi "https://doi.org/10.1007/978-3-319-90050-6_15" @default.
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