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ICANNGA
2007
Springer
161views Algorithms» more  ICANNGA 2007»
13 years 12 months ago
Evolutionary Induction of Decision Trees for Misclassification Cost Minimization
Abstract. In the paper, a new method of decision tree learning for costsensitive classification is presented. In contrast to the traditional greedy top-down inducer in the proposed...
Marek Kretowski, Marek Grzes
ICDM
2007
IEEE
131views Data Mining» more  ICDM 2007»
13 years 12 months ago
Predicting and Optimizing Classifier Utility with the Power Law
When data collection is costly and/or takes a significant amount of time, an early prediction of the classifier performance is extremely important for the design of the data minin...
Mark Last
AI50
2006
13 years 12 months ago
What Can AI Get from Neuroscience?
The human brain is the best example of intelligence known, with unsurpassed ability for complex, real-time interaction with a dynamic world. AI researchers trying to imitate its re...
Steve M. Potter
AUSAI
2003
Springer
13 years 11 months ago
On Why Discretization Works for Naive-Bayes Classifiers
We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBay...
Ying Yang, Geoffrey I. Webb
GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
13 years 11 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay