PR
2008
13 years 4 months ago
2008
Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
JMLR
2006
13 years 4 months ago
2006
In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
JUCS
2008
13 years 4 months ago
2008
: In this paper we propose a new approach to Swarm Intelligence called Two-Step Swarm Intelligence. The basic idea is to split the heuristic search performed by agents into two sta...
JUCS
2008
13 years 4 months ago
2008
: Feature selection methods are often applied in the context of document classification. They are particularly important for processing large data sets that may contain millions of...
JCP
2006
13 years 4 months ago
2006
Feature selection is one of key issues related with data pre-processing of classification task in a data mining process. Although many efforts have been done to improve typical fea...
JMM2
2008
13 years 4 months ago
2008
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...
IMDS
2006
13 years 4 months ago
2006
Purpose
BIOINFORMATICS
2006
13 years 4 months ago
2006
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
ALGORITHMICA
2006
13 years 4 months ago
2006
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
BMCBI
2008
13 years 4 months ago
2008
Background: Feature selection is a pattern recognition approach to choose important variables according to some criteria in order to distinguish or explain certain phenomena (i.e....