A Sparse PCA Approach to Clustering
classification
📊 stat.ME
stat.ML
keywords
methodclusteringdiscusssparseanalysisapproachcasecompare
read the original abstract
We discuss a clustering method for Gaussian mixture model based on the sparse principal component analysis (SPCA) method and compare it with the IF-PCA method. We also discuss the dependent case where the covariance matrix $\Sigma$ is not necessarily diagonal.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.