Dynamic and Scalable Evolutionary Data Mining: An Approach Based On a Self-Adaptive Multiple Expression Mechanism

Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving data streams created a crucial need for dynamic data mining. In this paper, we present a genetic algorithm based on a new representation mechanism, that allows several phenotypes to be simultaneously expressed to different degrees in the same chromosome