Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
In the context of classification problems, algorithms that generate multivariate trees are able to explore multiple representation languages by using decision tests based on a com...
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
A fuzzy c-means algorithm was adapted for analyzing microarray data. The adaptation consisted of initialization of fuzzy centroids using gene ontology information and the use of P...
Mingrui Zhang, Terry M. Therneau, Michael A. McKen...