Results 71 to 80 of about 414,017 (186)

Providing Diversity in K-Nearest Neighbor Query Results

, 2003
Given a point query Q in multi-dimensional space, K-Nearest Neighbor (KNN) queries return the K closest answers according to given distance metric in the database with respect to Q.
Haritsa, Jayant R., Jain, Anoop, Sarda, Parag   +2 more
core  

Enhanced Weighted K-Nearest Neighbor Positioning

2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring)
Peer ...
Li, Xinze, Al-Tous, Hanan, Hajri, Salah Eddine, Tirkkonen, Olav   +3 more
openaire   +2 more sources

Implementasi Algoritma K-Nearest Neighbor untuk Melakukan Klasifikasi Produk dari beberapa E-marketplace

JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2019
E-marketplace has gained popularity with the Indonesian society resulting in the increment of products offered. Consequently, customers require more effort to search for products. In this study, we classified products from several e-marketplaces.
Danny Sebastian
doaj   +1 more source

Angle-based Graph Neural Network Method for Anomaly Detection in High Dimensional Data [PDF]

Jisuanji gongcheng
In high-dimensional data spaces, most data are located at the edges of the high-dimensional space and distributed sparsely, resulting in the problem of "curse of dimensionality", which makes existing anomaly detection methods unable to ensure ...
Jun WANG, Huixia LAI, Yue WAN, Shi ZHANG
doaj   +1 more source

Fault Tolerant Clustering Revisited

, 2013
In discrete k-center and k-median clustering, we are given a set of points P in a metric space M, and the task is to output a set C \subseteq ? P, |C| = k, such that the cost of clustering P using C is as small as possible.
Kumar, Nirman, Raichel, Benjamin
core  

Random kernel k-nearest neighbors regression

Frontiers in Big Data
The 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. However, this method is susceptible to overfitting and fit discontinuity, which present significant challenges.
Patchanok Srisuradetchai, Korn Suksrikran   +1 more
openaire   +3 more sources

The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting [PDF]

This article gives the asymptotic properties of multivariate k-nearest neighbor regression estimators for dependent variables belonging to Rd, d > 1.
Dominique Guegan, Patrick Rakotomarolahy
core  

Detection of Android Malware in the Internet of Things through the K-Nearest Neighbor Algorithm. [PDF]

Sensors (Basel), 2023
Babbar H, Rani S, Sah DK, AlQahtani SA, Kashif Bashir A.   +4 more
europepmc   +1 more source

Delving into gene-set multiplex networks facilitated by a k-nearest neighbor-based measure of similarity. [PDF]

Comput Struct Biotechnol J, 2023
Zheng C, Wang M, Yamada R, Okada D.
europepmc   +1 more source

Rapid Identification of Material Defects Based on Pulsed Multifrequency Eddy Current Testing and the k-Nearest Neighbor Method. [PDF]

Materials (Basel), 2023
Grochowalski JM, Chady T.
europepmc   +1 more source