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» Learning to generalize for complex selection tasks
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AUSDM
2008
Springer
367views Data Mining» more  AUSDM 2008»
13 years 8 months ago
Categorical Proportional Difference: A Feature Selection Method for Text Categorization
Supervised text categorization is a machine learning task where a predefined category label is automatically assigned to a previously unlabelled document based upon characteristic...
Mondelle Simeon, Robert J. Hilderman
IDA
2009
Springer
14 years 1 months ago
Canonical Dual Approach to Binary Factor Analysis
Abstract. Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in B...
Ke Sun, Shikui Tu, David Yang Gao, Lei Xu
GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
14 years 7 days ago
Constructive induction and genetic algorithms for learning concepts with complex interaction
Constructive Induction is the process of transforming the original representation of hard concepts with complex interaction into a representation that highlights regularities. Mos...
Leila Shila Shafti, Eduardo Pérez
ICASSP
2011
IEEE
12 years 10 months ago
SVM feature selection for multidimensional EEG data
In many machine learning applications, like Brain - Computer Interfaces (BCI), only high-dimensional noisy data are available rendering the discrimination task non-trivial. In thi...
Nisrine Jrad, Ronald Phlypo, Marco Congedo
ICML
2007
IEEE
14 years 7 months ago
Sample compression bounds for decision trees
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Mohak Shah