Modelling the role of variables in model-based cluster analysis (Q1702292)

scientific article; zbMATH DE number 6844714

Language	Label	Description	Also known as
English	Modelling the role of variables in model-based cluster analysis	scientific article; zbMATH DE number 6844714

Statements

instance of

scholarly article

0 references

title

Modelling the role of variables in model-based cluster analysis (English)

0 references

0 references

0 references

0 references

Statistics and Computing

0 references

publication date

28 February 2018

0 references

full work available at URL

http://hdl.handle.net/11585/585288

0 references

zbMATH Keywords

clusterwise linear regression

0 references

EM algorithm

0 references

Gaussian mixture model

0 references

genetic algorithm

0 references

multiple cluster structure

0 references

variable selection

0 references

describes a project that uses

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

Variable selection for clustering and classification

0 references

Model-Based Gaussian and Non-Gaussian Clustering

0 references

A Generalized Clustering Problem, with Application to DNA Microarrays

0 references

Choosing models in model-based clustering and discriminant analysis

0 references

Variable Selection in Penalized Model‐Based Clustering Via Regularization on Grouped Parameters

0 references

A variable-selection heuristic for K-means clustering

0 references

Letter to the Editor

0 references

Q5262135

0 references

Genetic algorithms and their statistical applications: an introduction

0 references

A framework to uncover multiple alternative clusterings

0 references

A maximum likelihood methodology for clusterwise linear regression

0 references

Q4139463

0 references

Q3093206

0 references

Selection of Variables for Cluster Analysis and Classification Rules

0 references

Model-Based Clustering, Discriminant Analysis, and Density Estimation

0 references

Model-Based Clustering, Classification, and Density Estimation Using mclust in R

0 references

Clustering Objects on Subsets of Attributes (with Discussion)

0 references

Finite mixture and Markov switching models.

0 references

Penalized factor mixture analysis for variable selection in clustered data

0 references

Using mixtures in seemingly unrelated linear regression models with non-normal errors

0 references

Model-based methods to identify multiple cluster structures in a data set

0 references

Using conditional independence for parsimonious model-based Gaussian clustering

0 references

Weighting and selection of variables for cluster analysis

0 references

Q4692508

0 references

Q4264742

0 references

Pairwise Variable Selection for High-Dimensional Model-Based Clustering

0 references

Q3713407

0 references

Bayes Factors

0 references

Consistent estimation of the order of mixture models.

0 references

Greedy learning of latent tree models for multidimensional clustering

0 references

Model-based clustering based on sparse finite Gaussian mixtures

0 references

Variable Selection for Clustering with Gaussian Mixture Models

0 references

Variable selection in model-based clustering: a general variable role modeling

0 references

Finite mixture models

0 references

Modelling high-dimensional data by mixtures of factor analyzers

0 references

Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models

0 references

Finite mixture models and model-based clustering

0 references

A projection pursuit approach to variable selection.

0 references

Q3174113

0 references

Model-based clustering of high-dimensional data: variable selection versus facet determination

0 references

Estimating Mixtures of Normal Distributions and Switching Regressions

0 references

Variable Selection for Model-Based Clustering

0 references

Estimating the dimension of a model

0 references

Improved initialisation of model-based clustering using Gaussian hierarchical partitions

0 references

Identifying Multiple Cluster Structures in a Data Matrix

0 references

Multivariate linear regression with non-normal errors: a solution based on mixture models

0 references

Q3150922

0 references

Selection of variables in cluster analysis: An empirical comparison of eight procedures

0 references

Bayesian Variable Selection in Clustering High-Dimensional Data

0 references

Statistical Analysis of Financial Data in S-Plus

0 references

Dimensionally reduced model-based clustering through mixtures of factor mixture analyzers

0 references

Variable Selection for Model-Based High-Dimensional Clustering and Its Application to Microarray Data

0 references

A Framework for Feature Selection in Clustering

0 references

A new feature selection method for Gaussian mixture clustering

0 references

Penalized model-based clustering with unconstrained covariance matrices

0 references

Manly transformation in finite mixture modeling

0 references

Identifiers

zbMATH Open document ID

1384.62195

0 references

Mathematics Subject Classification ID

0 references

0 references

0 references

0 references

10.1007/S11222-017-9723-0

0 references

Sitelinks

Mathematics(1 entry)

mardi Publication:1702292