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» Stability of Feature Selection Algorithms
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DCC
2006
IEEE
16 years 2 months ago
Compression and Machine Learning: A New Perspective on Feature Space Vectors
The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
D. Sculley, Carla E. Brodley
117
Voted
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
15 years 8 months ago
Improving the human readability of features constructed by genetic programming
The use of machine learning techniques to automatically analyse data for information is becoming increasingly widespread. In this paper we examine the use of Genetic Programming a...
Matthew Smith, Larry Bull
114
Voted
GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
15 years 3 months ago
Evolving stable behavior in a spino-neuromuscular system model
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
Stanley Phillips Gotshall, Terry Soule
153
Voted
CANDC
2005
ACM
15 years 2 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
107
Voted
TPDS
1998
76views more  TPDS 1998»
15 years 2 months ago
Randomized Routing, Selection, and Sorting on the OTIS-Mesh
The Optical Transpose Interconnection System (OTIS) is a recently proposed model of computing that exploits the special features of both electronic and optical technologies. In th...
Sanguthevar Rajasekaran, Sartaj Sahni