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ICDAR
2003
IEEE
15 years 6 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ICIAP
2005
ACM
16 years 28 days ago
A Neural Adaptive Algorithm for Feature Selection and Classification of High Dimensionality Data
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Elisabetta Binaghi, Ignazio Gallo, Mirco Boschetti...
123
Voted
HAIS
2009
Springer
15 years 5 months ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...
KDD
1998
ACM
442views Data Mining» more  KDD 1998»
15 years 5 months ago
BAYDA: Software for Bayesian Classification and Feature Selection
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...
Petri Kontkanen, Petri Myllymäki, Tomi Siland...
92
Voted
IJON
2008
121views more  IJON 2008»
15 years 24 days ago
Locality sensitive semi-supervised feature selection
In many computer vision tasks like face recognition and image retrieval, one is often confronted with high-dimensional data. Procedures that are analytically or computationally ma...
Jidong Zhao, Ke Lu, Xiaofei He