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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5742505/ https://www.ncbi.nlm.nih.gov/pubmed/29376076 http://dx.doi.org/10.1155/2017/7560807 |