Consistency of the k-Nearest Neighbor Classifier for Spatially Dependent Data

被引：0
|
作者：
Ahmad Younso
Ziad Kanaya
Nour Azhari
机构：
[1] Université Montpellier,INRAE, Institut Agro, MISTEA
[2] Damascus University,Department of Mathematical Statistics, Faculty of Sciences
[3] Tishreen University,Department of Mathematics, Faculty of Sciences
来源：
Communications in Mathematics and Statistics | 2023年 / 11卷
关键词：
Bayes rule; Spatial data; Training data; -nearest neighbor rule; Mixing condition; Consistency; 62H11; 62G08; 62G20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The purpose of this paper is to investigate the k-nearest neighbor classification rule for spatially dependent data. Some spatial mixing conditions are considered, and under such spatial structures, the well known k-nearest neighbor rule is suggested to classify spatial data. We established consistency and strong consistency of the classifier under mild assumptions. Our main results extend the consistency result in the i.i.d. case to the spatial case.
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页码：503 / 518
页数：15
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