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GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
13 years 9 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
ACSW
2004
13 years 7 months ago
Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...
William D. Smart, Mengjie Zhang
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
13 years 12 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
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
13 years 9 months ago
Using genetic programming to classify node positive patients in bladder cancer
Nodal staging has been identified as an independent indicator of prognosis. Quantitative RT-PCR data was taken for 70 genes associated with bladder cancer and genetic programming ...
Arpit A. Almal, Anirban P. Mitra, Ram H. Datar, Pe...
CEC
2010
IEEE
13 years 3 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...