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» Robust bounds for classification via selective sampling
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ICMCS
2005
IEEE
129views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Feature Selection and Stacking for Robust Discrimination of Speech, Monophonic Singing, and Polyphonic Music
In this work we strive to find an optimal set of acoustic features for the discrimination of speech, monophonic singing, and polyphonic music to robustly segment acoustic media st...
Björn Schuller, Brüning J. B. Schmitt, D...
ICPR
2006
IEEE
14 years 8 months ago
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...
ICASSP
2009
IEEE
14 years 2 months ago
Microarray classification using block diagonal linear discriminant analysis with embedded feature selection
In this paper, block diagonal linear discriminant analysis (BDLDA) is improved and applied to gene expression data. BDLDA is a classification tool with embedded feature selection...
Lingyan Sheng, Roger Pique-Regi, Shahab Asgharzade...
BMCBI
2004
205views more  BMCBI 2004»
13 years 7 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
CSDA
2008
126views more  CSDA 2008»
13 years 7 months ago
A new genetic algorithm in proteomics: Feature selection for SELDI-TOF data
Mass spectrometry from clinical specimens is used in order to identify biomarkers in a diagnosis. Thus, a reliable method for both feature selection and classification is required...
Christelle Reynès, Robert Sabatier, Nicolas...