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K Important Neighbors: A Novel Approach to Binary Classification in High Dimensional Data

K nearest neighbors (KNN) are known as one of the simplest nonparametric classifiers but in high dimensional setting accuracy of KNN are affected by nuisance features. In this study, we proposed the K important neighbors (KIN) as a novel approach for binary classification in high dimensional problem...

詳細記述

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書誌詳細
出版年:Biomed Res Int
主要な著者: Raeisi Shahraki, Hadi, Pourahmad, Saeedeh, Zare, Najaf
フォーマット: Artigo
言語:Inglês
出版事項: Hindawi 2017
主題:
オンライン・アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC5742505/
https://ncbi.nlm.nih.gov/pubmed/29376076
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/7560807
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