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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 Learning with Graph Neural Networks
Mathematics, 2021 k-nearest neighbor (kNN) is a widely used learning algorithm for supervised learning tasks. In practice, the main challenge when using kNN is its high sensitivity to its hyperparameter setting, including the number of nearest neighbors k, the distance ...
Seokho Kang
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A generalized fuzzy k-nearest neighbor regression model based on Minkowski distance
Granular Computing, 2021 The fuzzy k-nearest neighbor (FKNN) algorithm, one of the most well-known and effective supervised learning techniques, has often been used in data classification problems but rarely in regression settings. This paper introduces a new, more general fuzzy
Mahinda Mailagaha Kumbure, P. Luukka
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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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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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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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, 2020 In this paper, sixty-eight research articles published between 2000 and 2017 as well as textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN), Support Vector Machines (SVM), Random Forest (RF) and Neural Network (NN) as the ...
E. Y. Boateng, Joseph Otoo., D. Abaye
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, 2021 The purpose of this study was to examine the results of the prediction of breast cancer, which have been classified based on two types of breast cancer, malignant and benign.
Henderi Henderi +2 more
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Ilkom Jurnal Ilmiah, 2023 Academic services are actions taken by state and private universities to provide convenience for student’s academic activities. During the current covid-19 pandemic, every university remains active in academic activities.
Andi Bode +2 more
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