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ICDM
2008
IEEE
182views Data Mining» more  ICDM 2008»
14 years 3 months ago
Multiple-Instance Regression with Structured Data
We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) op...
Kiri L. Wagstaff, Terran Lane, Alex Roper
ICDM
2003
IEEE
104views Data Mining» more  ICDM 2003»
14 years 1 months ago
Localized Prediction of Continuous Target Variables Using Hierarchical Clustering
In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
PAKDD
2007
ACM
158views Data Mining» more  PAKDD 2007»
14 years 2 months ago
Density-Sensitive Evolutionary Clustering
In this study, we propose a novel evolutionary algorithm-based clustering method, named density-sensitive evolutionary clustering (DSEC). In DSEC, each individual is a sequence of ...
Maoguo Gong, Licheng Jiao, Ling Wang, Liefeng Bo
BMCBI
2007
166views more  BMCBI 2007»
13 years 8 months ago
How to decide which are the most pertinent overly-represented features during gene set enrichment analysis
Background: The search for enriched features has become widely used to characterize a set of genes or proteins. A key aspect of this technique is its ability to identify correlati...
Roland Barriot, David J. Sherman, Isabelle Dutour
DAS
2008
Springer
13 years 10 months ago
A Comparison of Clustering Methods for Word Image Indexing
In this paper we explore the effectiveness of three clustering methods used to perform word image indexing. The three methods are: the Self-Organazing Map (SOM), the Growing Hiera...
Simone Marinai, Emanuele Marino, Giovanni Soda