Abstract
We propose an intelligent data mining (DM) assistant that will combine planning and meta-learning to provide support to users of virtual DM laboratory. A knowledge-driven planner will rely on a data mining ontology to plan the knowledge discovery workflow and determine the set of valid operators for each step of this workflow. A probabilistic meta-learner will select the most appropriate operators by using relational similarity measures and kernel functions over records of past sessions meta-data stored in a DM experiments repository.
Kalousis, A