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» Objective reduction using a feature selection technique
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IBERAMIA
2004
Springer
14 years 1 months ago
Applying Rough Sets Reduction Techniques to the Construction of a Fuzzy Rule Base for Case Based Reasoning
Early work on Case Based Reasoning reported in the literature shows the importance of soft computing techniques applied to different stages of the classical 4-step CBR life cycle. ...
Florentino Fdez-Riverola, Fernando Díaz, Ju...
ICASSP
2008
IEEE
14 years 2 months ago
Discriminative feature selection for hidden Markov models using Segmental Boosting
We address the feature selection problem for hidden Markov models (HMMs) in sequence classification. Temporal correlation in sequences often causes difficulty in applying featur...
Pei Yin, Irfan A. Essa, Thad Starner, James M. Reh...
ICPR
2004
IEEE
14 years 9 months ago
Feature Subset Selection using ICA for Classifying Emphysema in HRCT Images
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
Mithun Nagendra Prasad, Arcot Sowmya, Inge Koch
TMI
1998
134views more  TMI 1998»
13 years 7 months ago
Speckle Reduction and Contrast Enhancement of Echocardiograms via Multiscale Nonlinear Processing
Abstract— This paper presents an algorithm for speckle reduction and contrast enhancement of echocardiographic images. Within a framework of multiscale wavelet analysis, we apply...
Xuli Zong, Andrew Laine, Edward A. Geiser
SAC
2006
ACM
14 years 1 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal