C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining and knowledge discovery in databases
Communications of the ACM
Communications of the ACM
The impact of poor data quality on the typical enterprise
Communications of the ACM
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Machine Learning
Data Mining: the search for knowledge in databases.
Data Mining: the search for knowledge in databases.
| Hi-index | 0.01 |
Knowledge discovery is a new discipline that applies machine learning techniques to large real-world databases to extract knowledge from the data. This knowledge is often expressed as rules modeling the data. Genetic algorithms (GA) are a unique method for evolving high quality solutions from a potentially huge search space of possible solutions. This technique uses a simulated process of natural selection rather than a simulated reasoning process. Genetic algorithms are uniquely suited to data mining problems due to the inductive nature of the problem. This paper describes two GA-based data mining systems, GA-MINIR, a pure GA technique, and DOGMA, a hybrid technique, using GAs to improve on rules generated by another classifier. It also discusses the difficulty of formally analyzing a genetic algorithm in order to compare it with more conventional methods of solving the same problem.