A feasible \(k\)-means kernel trick under non-Euclidean feature space
type: Item
instance of: scholarly article
title: A feasible \(k\)-means kernel trick under non-Euclidean feature space
zbMATH Open document ID: 1467.62089
author: Mieczysław Kłopotek
author: Sławomir T. Wierzchoń
author: Robert A. Kłopotek
published in: International Journal of Applied Mathematics and Computer Science
publication date: 2021-05-03T00:00:00Z
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62H30
zbMATH DE Number: 7342325
zbMATH Keywords: kernel methods
zbMATH Keywords: \(k\)-means
zbMATH Keywords: clustering
zbMATH Keywords: non-Euclidean feature space
zbMATH Keywords: Gower/Legendre theorem
describes a project that uses: sedaR
MaRDI profile type: Publication
full work available at URL: article-p703.xml
OpenAlex ID: W3120583973
cites work: On Euclidean distance matrices
cites work: The analytical solution of the additive constant problem
cites work: Multidimensional scaling.
cites work: Q3954439
cites work: Properties of Euclidean and non-Euclidean distance matrices
cites work: Metric and Euclidean properties of dissimilarity coefficients
cites work: Computing a nearest symmetric positive semidefinite matrix
cites work: Kernel methods in machine learning
cites work: Regression function and noise variance tracking methods for data streams with concept drift
cites work: On the Existence of Kernel Function for Kernel-Trick of k-Means in the Light of Gower Theorem
cites work: Q4951438
cites work: Some boundary conditions for a monotone analysis of symmetric matrices
cites work: Times series averaging and denoising from a probabilistic perspective on time-elastic kernels
cites work: The complexity of the matrix eigenproblem
cites work: The Dissimilarity Representation for Pattern Recognition
cites work: 10.1162/15324430260185592
cites work: A Convex Matrix Optimization for the Additive Constant Problem in Multidimensional Scaling with Application to Locally Linear Embedding
cites work: Indefinite Proximity Learning: A Review
cites work: Metric Spaces and Positive Definite Functions
cites work: An introduction to support vector machines and other kernel-based learning methods.
cites work: Partial distance correlation with methods for dissimilarities
cites work: Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning
cites work: Modern Algorithms of Cluster Analysis
DOI: 10.34768/AMCS-2020-0052
description: scientific article; zbMATH DE number 7342325