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Random kernel k-nearest neighbors regression [PDF]
Frontiers in Big DataThe k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big data contexts.
Patchanok Srisuradetchai +1 more
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Compressed kNN: K-Nearest Neighbors with Data Compression [PDF]
Entropy, 2019 The kNN (k-nearest neighbors) classification algorithm is one of the most widely used non-parametric classification methods, however it is limited due to memory consumption related to the size of the dataset, which makes them impractical to apply to ...
Jaime Salvador–Meneses +2 more
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Studi Analisis Pengenalan Pola Tulisan Tangan Angka Arabic (Indian) menggunakan Metode K- Nearest Neighbors dan Connected Component Labeling [PDF]
Dinamika Rekayasa, 2016 Handwriting refers to the result of writing by hand (not typed). The writing style of people are not the same. One of the United Nations official languages, Arabic, has a numerical system known as Arabic (Indian) numeral.
Roni Akbar, Eko Adi Sarwoko
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Chromatic $k$-Nearest Neighbor Queries
Journal of Computational Geometry, 2022 37 pages, 9 ...
van der Horst, Thijs +2 more
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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
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Recognizing steel elements with BRDF and k-nearest neighbors [PDF]
Metrology and Measurement Systems, 2023 The paper deals with analysis of recognition of surface quality with reflective structures. Such surfaces are common in metallic materials cut using a saw or polished. There are no easy methods to identify such elements after machining.
Adam Ciszkiewicz +2 more
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Fast Approximate Complete-data k-nearest-neighbor Estimation
Austrian Journal of Statistics, 2020 We introduce a fast method to estimate the complete-data set of k-nearest-neighbors.This is equivalent to finding an estimate of the k-nearest-neighbor graph of the data. The method relies on random normal projections.
Alejandro Murua, Nicolas Wicker
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MGR: Efficiently Processing Maximal Group Reverse k Nearest Neighbors Queries
IEEE Access, 2022 Given a set of facilities and a set of clients, a reverse $k$ nearest neighbors ( $\text{R}k$ NN) query returns every client for which the query facility is one of the $k$ -closest facilities.
Xin Meng +3 more
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Media Statistika, 2023 In machine learning study, classification analysis aims to minimize misclassification and also maximize the results of prediction accuracy. The main characteristic of this classification problem is that there is one class that significantly exceeds the ...
Jus Prasetya, Abdurakhman Abdurakhman
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IEEE Access, 2020 Enhancing the accuracy of indoor visible light positioning systems with simple, real-time, and stable methods is one of the interesting challenges in recent research.
Huy Quang Tran, Cheolkeun Ha
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