Results 21 to 30 of about 131,772 (305)
IMPLEMENTATION OF GAIN RATIO AND K-NEAREST NEIGHBOR FOR CLASSIFICATION OF STUDENT PERFORMANCE
Pilar Nusa Mandiri, 2020 Predicting student performance is very useful in analyzing weak students and providing support to students who face difficulties. However, the work done by educators has not been effective enough in identifying factors that affect student performance ...
Tyas Setiyorini, Rizky Tri Asmono
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Approximate $k$-Nearest Neighbor Graph on Moving Points [PDF]
Transactions on Combinatorics, 2023 In this paper, we introduce an approximation for the $k$-nearest neighbor graph ($k$-NNG) on a point set $P$ in $\mathbb{R}^d$. For any given $\varepsilon>0$, we construct a graph, that we call the \emph{approximate $k$-NNG}, where the edge with the $i ...
Zahed Rahmati
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K-nearest neighbor imputation for missing value in hepatitis data
, 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
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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
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, 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
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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
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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
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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
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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
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Continuous Nearest Neighbor Queries over Sliding Windows [PDF]
, 2007 —This paper studies continuous monitoring of nearest neighbor (NN) queries over sliding window streams. According to this model, data points continuously stream in the system, and they are considered valid only while they belong to a sliding window that ...
Papadias, Dimitris +3 more
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