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» Obtaining Best Parameter Values for Accurate Classification
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IJON
2000
81views more  IJON 2000»
13 years 7 months ago
Initialization by selection for wavelet network training
We present an original initialization procedure for the parameters of feedforward wavelet networks, prior to training by gradient-based techniques. It takes advantage of wavelet f...
Yacine Oussar, Gérard Dreyfus
TMI
2010
206views more  TMI 2010»
13 years 2 months ago
Random Subspace Ensembles for fMRI Classification
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
Ludmila I. Kuncheva, Juan José Rodrí...
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
13 years 5 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
TIT
2010
118views Education» more  TIT 2010»
13 years 2 months ago
Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis
Error estimation must be used to find the accuracy of a designed classifier, an issue that is critical in biomarker discovery for disease diagnosis and prognosis in genomics and p...
Amin Zollanvari, Ulisses Braga-Neto, Edward R. Dou...
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