Weighted co-association rate-based Laplacian regularized label description for semi-supervised regression
type: Item
instance of: scholarly article
title: Weighted co-association rate-based Laplacian regularized label description for semi-supervised regression
zbMATH Open document ID: 1479.62048
author: Jaehong Yu
author: Youngdoo Son
published in: Information Sciences
publication date: 2021-11-30T00:00:00Z
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 62J02
Mathematics Subject Classification ID: 62-08
zbMATH DE Number: 7436263
zbMATH Keywords: label-descriptive function
zbMATH Keywords: semi-supervised regression
zbMATH Keywords: smoothness regularization
zbMATH Keywords: weighted co-association rate
describes a project that uses: AS 136
describes a project that uses: Spearmint
MaRDI profile type: Publication
full work available at URL: j.ins.2020.09.015
OpenAlex ID: W3087009257
cites work: Q3174044
cites work: Q4003026
cites work: Error bounds of multi-graph regularized semi-supervised classification
cites work: Algorithm AS 136: A K-Means Clustering Algorithm
cites work: Unsupervised feature selection using clustering ensembles and population based incremental learning algorithm
cites work: Robust non-negative sparse graph for semi-supervised multi-label learning with missing labels
cites work: Q5617409
cites work: Q5509408
cites work: Semi-supervised sparse feature selection via graph Laplacian based scatter matrix for regression problems
cites work: Consensus rate-based label propagation for semi-supervised classification
cites work: An ensemble feature ranking algorithm for clustering analysis
cites work: A clustering ensemble: two-level-refined co-association matrix with path-based transformation
DOI: 10.1016/J.INS.2020.09.015
description: scientific article; zbMATH DE number 7436263