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» Classifier Selection Based on Data Complexity Measures
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ESANN
2006
14 years 11 months ago
Adaptive Sensor Modelling and Classification using a Continuous Restricted Boltzmann Machine (CRBM)
A probabilistic, ``neural'' approach to sensor modelling and classification is described, performing local data fusion in a wireless system for embedded sensors using a ...
Tong Boon Tang, Alan F. Murray
ECCV
2004
Springer
15 years 3 months ago
AQUATICS Reconstruction Software: The Design of a Diagnostic Tool Based on Computer Vision Algorithms
Computer vision methods can be applied to a variety of medical and surgical applications, and many techniques and algorithms are available that can be used to recover 3D shapes and...
Andrea Giachetti, Gianluigi Zanetti
ISNN
2004
Springer
15 years 3 months ago
Sparse Bayesian Learning Based on an Efficient Subset Selection
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale pr...
Liefeng Bo, Ling Wang, Licheng Jiao
MCS
2004
Springer
15 years 3 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel
AI
2004
Springer
14 years 9 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu