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ICANNGA
2007
Springer
161views Algorithms» more  ICANNGA 2007»
15 years 5 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»
15 years 5 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
15 years 5 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
15 years 5 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»
15 years 5 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