• Publications
  • Influence
Fuzzy decision trees: issues and methods
  • C. Janikow
  • Medicine, Computer Science
  • IEEE Trans. Syst. Man Cybern. Part B
  • 1 February 1998
TLDR
We present another modification, aimed at combining symbolic decision trees with approximate reasoning offered by fuzzy representation. Expand
  • 638
  • 52
  • PDF
Handling Constraints in Genetic Algorithms
  • 399
  • 11
A Knowledge-Intensive Genetic Algorithm for Supervised Learning
Supervised learning in attribute-based spaces is one of the most popular machine learning problems studied and, consequently, has attracted considerable attention of the genetic algorithm community.Expand
  • 126
  • 9
A knowledge-intensive genetic algorithm for supervised learning
  • C. Janikow
  • Computer Science
  • Machine Learning
  • 1 November 1993
TLDR
Abstracting the genetic algorithm to the problem level, described here for the supervised inductive learning, can be also extended to other domains and tasks, since it provides a framework for combining recently popular genetic algorithm methods with traditional problem-solving methodologies. Expand
  • 170
  • 7
  • PDF
A modified genetic algorithm for optimal control problems
Abstract This paper studies the application of a genetic algorithm to discrete-time optimal control problems. Numerical results obtained here are compared with ones yielded by GAMS, a system forExpand
  • 229
  • 7
GENOCOP: a genetic algorithm for numerical optimization problems with linear constraints
TLDR
We present a new approach to solving numerical optimization problems with linear constraints with genetic algorithms, based on genetic algorithms. Expand
  • 140
  • 6
Genetic algorithms for numerical optimization
Genetic algorithms (GAs) are stochastic adaptive algorithms whose search method is based on simulation of natural genetic inheritance and Darwinian striving for survival. They can be used to findExpand
  • 99
  • 3
Inductive learning of decision rules from attribute-based examples: a knowledge-intensive genetic algorithm approach
TLDR
We present a modified genetic algorithm designed for the problem of supervised inductive learning in feature-based spaces which utilizes domain dependent task-specific knowledge. Expand
  • 29
  • 3
Exemplar learning in fuzzy decision trees
  • C. Janikow
  • Mathematics
  • Proceedings of IEEE 5th International Fuzzy…
  • 8 September 1996
Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism,Expand
  • 59
  • 2
  • PDF