A unified variational methodology is developed for classification and clustering problems, and tested in the classification of tumors from gene expression data. It is based on flu...
J. P. Agnelli, M. Cadeiras, E. G. Tabak, C. V. Tur...
Background: During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the...
Abstract. Approximate string matching is a fundamental and challenging problem in computer science, for which a fast algorithm is highly demanded in many applications including tex...
We introduce a new ensemble method based on decision tree to discover significant and diversified rules for subtype classification of childhood acute lymphoblastic leukemia, a ...
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...