Results 11 to 20 of about 9,360,077 (298)
Chromatic k-nearest neighbor queries
Journal of Computational Geometry, 2022 Let $P$ be a set of $n$ colored points in $\mathbb{R}^d$. We develop efficient data structures that store $P$ and can answer chromatic $k$-nearest neighbor ($k$-NN) queries.
Thijs van der Horst +2 more
doaj +11 more sources
Weighted K-Nearest Neighbor revisited
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 In this paper we show that weighted K-Nearest Neighbor, a variation of the classic K-Nearest Neighbor, can be reinterpreted from a classifier combining perspective, specifically as a fixed combiner rule, the sum rule. Subsequently, we experimentally demonstrate that it can be rather beneficial to consider other combining schemes as well. In particular,
BICEGO, Manuele, Loog, M.
openaire +4 more sources
K-nearest neighbor imputation for missing value in hepatitis data [PDF]
, 2022 There has been a growing occurrence of errors in a dataset, one of which is the incomplete data on an attribute or commonly acknowledged as a missing value, affecting the results of an analysis conducted for researchers.
Syafaah, Lailis +2 more
core +3 more sources
Modernizing k‐nearest neighbors
Stat, 2021 The k‐nearest neighbors (k‐NN) method is one of the oldest statistical/machine learning techniques. It is included in virtually every major package, such as caret, parsnip, mlr3 and scikit‐learn. Yet those packages do not go beyond the basics. With today's high‐speed computation capability, k‐NN can be made much more powerful.
Robin Elizabeth Yancey +2 more
openaire +1 more source
K-Nearest Neighbor with K-Fold Cross Validation and Analytic Hierarchy Process on Data Classification [PDF]
, 2021 This study analyzes the performance of the k-Nearest Neighbor method with the k-Fold Cross Validation algorithm as an evaluation model and the Analytic Hierarchy Process method as feature selection for the data classification process in order to obtain ...
Zarlis, Muhammad +5 more
core +1 more source
REKOMENDASI KOMODITAS EKSPOR MENGGUNAKAN K-NEAREST NEIGHBOR
JSiI (Jurnal Sistem Informasi), 2023 Indonesia memiliki produksi komoditas yang beragam dan melimpah dengan nilai ekspor yang luar biasa, khususnya pada bidang agrikultur. Banyaknya komoditas yang tersedia, membuat para eksportir maupun calon ekportir mengalami kesulitan menentukan ...
Sony Simare-mare, Henry Pandia
doaj +1 more source
Sparse Coefficient-Based ${k}$ -Nearest Neighbor Classification
IEEE Access, 2017 K-nearest neighbor rule (KNN) and sparse representation (SR) are widely used algorithms in pattern classification. In this paper, we propose two new nearest neighbor classification methods, in which the novel weighted voting methods are developed for ...
Hongxing Ma +4 more
doaj +1 more source
A new locally adaptive K-nearest centroid neighbor classification based on the average distance
Connection Science, 2022 The classification performance of a k-nearest neighbour (KNN) method is dependent on the choice of the k neighbours of a query. However, it is difficult to optimise the performance of KNN by choosing appropriate neighbours and an appropriate value of k ...
Benqiang Wang, Shunxiang Zhang
doaj +1 more source
Weighted k-Nearest-Neighbor Techniques and Ordinal Classification [PDF]
, 2004 In the field of statistical discrimination k-nearest neighbor classification is a well-known, easy and successful method. In this paper we present an extended version of this technique, where the distances of the nearest neighbors can be taken into ...
Schliep, Klaus +3 more
core +1 more source
Feature Selection and Weighting by Nearest Neighbor Ensembles [PDF]
, 2008 In the field of statistical discrimination nearest neighbor methods are a well known, quite simple but successful nonparametric classification tool. In higher dimensions, however, predictive power normally deteriorates. In general, if some covariates are
Gertheiss, Jan +3 more
core +1 more source