Pages that link to "Item:Q961872"

The following pages link to Variable selection in model-based clustering: a general variable role modeling (Q961872):

Displaying 41 items.

• Sparse clustering of functional data (Q61004) (← links)
• A mixture of generalized hyperbolic factor analyzers (Q108960) (← links)
• Variable selection for model-based clustering using the integrated complete-data likelihood (Q133915) (← links)
• Model-based clustering for conditionally correlated categorical data (Q269537) (← links)
• Sparse optimal discriminant clustering (Q294233) (← links)
• Using mixtures in seemingly unrelated linear regression models with non-normal errors (Q340854) (← links)
• Clustering student skill set profiles in a unit hypercube using mixtures of multivariate betas (Q369354) (← links)
• Variable selection in model-based discriminant analysis (Q634551) (← links)
• Multivariate linear regression with non-normal errors: a solution based on mixture models (Q637985) (← links)
• High-dimensional variable selection with the plaid mixture model for clustering (Q722745) (← links)
• Using conditional independence for parsimonious model-based Gaussian clustering (Q746302) (← links)
• Variable selection for mixed data clustering: application in human population genomics (Q779017) (← links)
• Robust variable selection for model-based learning in presence of adulteration (Q830086) (← links)
• Selection of variables in cluster analysis: An empirical comparison of eight procedures (Q946679) (← links)
• Variable selection in model-based clustering: a general variable role modeling (Q961872) (← links)
• Model-based clustering of high-dimensional data: a review (Q1621282) (← links)
• Model-based biclustering of clickstream data (Q1660186) (← links)
• Modelling the role of variables in model-based cluster analysis (Q1702292) (← links)
• Variable selection methods for model-based clustering (Q1749770) (← links)
• Simultaneous dimension reduction and clustering via the NMF-EM algorithm (Q2036153) (← links)
• High-dimensional clustering via random projections (Q2129311) (← links)
• Discriminative variable selection for clustering with the sparse Fisher-EM algorithm (Q2259731) (← links)
• Unifying data units and models in (co-)clustering (Q2418082) (← links)
• Variable selection in model-based clustering and discriminant analysis with a regularization approach (Q2418093) (← links)
• Enhancing the selection of a model-based clustering with external categorical variables (Q2418394) (← links)
• A stochastic algorithm for probabilistic independent component analysis (Q2428739) (← links)
• Variable selection in model-based clustering using multilocus genotype data (Q2442772) (← links)
• Special issue on variable selection and robust procedures (Q2445742) (← links)
• Model-based clustering (Q2628064) (← links)
• Unobserved classes and extra variables in high-dimensional discriminant analysis (Q2673359) (← links)
• Group-wise shrinkage estimation in penalized model-based clustering (Q2680189) (← links)
• Cluster‐Specific Variable Selection for Product Partition Models (Q3460664) (← links)
• A simple model‐based approach to variable selection in classification and clustering (Q5256376) (← links)
• SelvarClustMV: variable selection approach in model-based clustering allowing for missing values (Q5262071) (← links)
• (Q5262135) (← links)
• (Q5447540) (← links)
• A survey on model-based co-clustering: high dimension and estimation challenges (Q6138123) (← links)
• On variable selection in matrix mixture modelling (Q6541565) (← links)
• Challenges in model-based clustering (Q6562689) (← links)
• A Bayesian hierarchical hidden Markov model for clustering and gene selection: application to kidney cancer gene expression data (Q6625479) (← links)
• Variable selection for hidden Markov models with continuous variables and missing data (Q6657928) (← links)