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» Measuring the Complexity of Classification Problems
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FLAIRS
2007
13 years 10 months ago
An Extended Neural Gas Model for Efficient Data Mining Tasks
This paper presents a numerical association rule extraction method that is based on original quality measures which evaluate to what extent a numerical classification model behave...
Jean-Charles Lamirel, Shadi Al Shehabi
SETN
2004
Springer
14 years 1 months ago
A Meta-classifier Approach for Medical Diagnosis
Abstract. Single classifiers, such as Neural Networks, Support Vector Machines, Decision Trees and other, can be used to perform classification of data for relatively simple proble...
George L. Tsirogiannis, Dimitrios S. Frossyniotis,...
ICASSP
2011
IEEE
12 years 11 months ago
Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals
In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly spa...
Shubha Shedthikere, Ananthanarayanan Chockalingam
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 15 days ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
AIPS
2008
13 years 10 months ago
Causal Graphs and Structurally Restricted Planning
The causal graph is a directed graph that describes the variable dependencies present in a planning instance. A number of papers have studied the causal graph in both practical an...
Hubie Chen, Omer Giménez