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KDD
2010
ACM
326views Data Mining» more  KDD 2010»
13 years 2 months ago
Document clustering via dirichlet process mixture model with feature selection
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
Guan Yu, Ruizhang Huang, Zhaojun Wang
JMM2
2008
124views more  JMM2 2008»
13 years 4 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
CCECE
2006
IEEE
13 years 10 months ago
Breast Cancer Prognosis via Gaussian Mixture Regression
This paper compares the performance of classification and regression trees (CART), multivariate adaptive regression splines (MARS), and a Gaussian mixture regressor (GMR) method ...
Tiago H. Falk, Hagit Shatkay, Wai-Yip Chan
ICPR
2004
IEEE
14 years 5 months ago
Iterative Figure-Ground Discrimination
Figure-ground discrimination is an important problem in computer vision. Previous work usually assumes that the color distribution of the figure can be described by a low dimensio...
Liang Zhao, Larry S. Davis
BMCBI
2004
181views more  BMCBI 2004»
13 years 4 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon