Speculate-correct error bounds for k-nearest neighbor classifiers
نویسندگان
چکیده
منابع مشابه
Error minimizing algorithms for nearest neighbor classifiers
Stack Filters define a large class of discrete nonlinear filter first introduced in image and signal processing for noise removal. In recent years we have suggested their application to classification problems, and investigated their relationship to other types of discrete classifiers such as Decision Trees. In this paper we focus on a continuous domain version of Stack Filter Classifiers which...
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A novel approach for k-nearest neighbor (k-NN) searching with Euclidean metric is described. It is well known that many sophisticated algorithms cannot beat the brute-force algorithm when the dimensionality is high. In this study, a probably correct approach, in which the correct set of k-nearest neighbors is obtained in high probability, is proposed for greatly reducing the searching time. We ...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2019
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-019-05814-1