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JMLR
2010
115views more  JMLR 2010»
13 years 3 months ago
O-IPCAC and its Application to EEG Classification
In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...
BMCBI
2008
109views more  BMCBI 2008»
13 years 8 months ago
MetaFIND: A feature analysis tool for metabolomics data
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Kenneth Bryan, Lorraine Brennan, Padraig Cunningha...
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
11 years 11 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
CEC
2008
IEEE
14 years 3 months ago
Reduced polynomial neural swarm net for classification task in data mining
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...
Bijan Bihari Misra, Satchidananda Dehuri, Pradipta...
ICML
2000
IEEE
14 years 9 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall