Search Results for author: Eric Bair

Found 4 papers, 0 papers with code

Non-Parametric Cluster Significance Testing with Reference to a Unimodal Null Distribution

no code implementations5 Oct 2016 Erika S. Helgeson, Eric Bair

Cluster analysis is an unsupervised learning strategy that can be employed to identify subgroups of observations in data sets of unknown structure.

Clustering Density Estimation

Biclustering Via Sparse Clustering

no code implementations11 Jul 2014 Qian Liu, Guanhua Chen, Michael R. Kosorok, Eric Bair

This framework can be used to identify biclusters that differ with respect to the means of the features, the variance of the features, or more general differences.

Clustering

Semi-supervised clustering methods

no code implementations1 Jul 2013 Eric Bair

Conventional clustering methods are unsupervised, meaning that there is no outcome variable nor is anything known about the relationship between the observations in the data set.

Clustering

Identification of relevant subtypes via preweighted sparse clustering

no code implementations13 Apr 2013 Sheila Gaynor, Eric Bair

Conventional methods may identify clusters associated with these high-variance features when one wishes to obtain secondary clusters that are more interesting biologically or more strongly associated with a particular outcome of interest.

Clustering

Cannot find the paper you are looking for? You can Submit a new open access paper.