E2K: Evolution to Knowledge
TR No.: 2006022 | Download PDF | Download PS
Abstract:
Evolution to Knowledge (E2K) is a set of Data to
Knowledge (D2K) modules and itineraries that perform genetic
algorithms (GA) and genetics-based machine learning (GBML) related
tasks. The goal of E2K is to fold: simplify the process of building
GA/GBML related tasks, and provide a simple exploratory workbench for
the evolutionary computation community to help users to interact with
evolutionary processes. It can help to create complex tasks or help
the newcomer to get familiarized and trained with the evolutionary
methods and techniques provided. Moreover, due to its integration
into D2K, the creation of combined data mining and evolutionary task
can be effortlessly done via the visual programming paradigm provided
by the workflow environment and also wrap other evolutionary
computation software.
Posted: April 20th, 2006 under Genetic algorithms.
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