ASCRClu: an adaptive subspace combination and reduction algorithm for clustering of high-dimensional data
Sign Up to like & getrecommendations! Published in 2020 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-020-00884-7
Abstract: The curse of dimensionality in high-dimensional data is one of the major challenges in data clustering. Recently, a considerable amount of literature has been published on subspace clustering to address this challenge. The main objective… read more here.
Keywords: combination; high dimensional; subspace clustering; dimensional data ... See more keywords
Clustering High-dimensional data via feature selection.
Sign Up to like & getrecommendations! Published in 2022 at "Biometrics"
DOI: 10.1111/biom.13665
Abstract: High-dimensional clustering analysis is a challenging problem in statistics and machine learning, with broad applications such as the analysis of microarray data and RNA-seq data. In this paper, we propose a new clustering procedure called… read more here.
Keywords: high dimensional; clustering high; dimensional data; feature selection ... See more keywords