Multi-Partitions Subspace Clustering
In model based clustering, it is often supposed that only one clustering latent variable explains the heterogeneity of the whole dataset. However, in many cases several latent variables could explain the heterogeneity of the data at hand. Finding such class variables could result in a richer interpr...
Main Author: | Vincent Vandewalle |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-04-01
|
Series: | Mathematics |
Subjects: | |
Online Access: | https://www.mdpi.com/2227-7390/8/4/597 |
Similar Items
-
An Integrated Approach for Making Inference on the Number of Clusters in a Mixture Model
by: Erlandson Ferreira Saraiva, et al.
Published: (2019-10-01) -
flexCWM: A Flexible Framework for Cluster-Weighted Models
by: Angelo Mazza, et al.
Published: (2018-09-01) -
Una aplicación del método jerárquico de mezclas para la clasificación de los municipios venezolanos según variables socioeconómicas
by: FREDDY OMAR LÓPEZ QUINTERO, et al.
Published: (2009-12-01) -
Multi-Scale Deep Subspace Clustering With Discriminative Learning
by: Jiao Wang, et al.
Published: (2022-01-01) -
Model-Based Clustering, Classification, and Discriminant Analysis Using the Generalized Hyperbolic Distribution: MixGHD R package
by: Cristina Tortora, et al.
Published: (2021-05-01)