Sciweavers

Share
CIDM
2009
IEEE

Evolving decision trees using oracle guides

9 years 1 months ago
Evolving decision trees using oracle guides
—Some data mining problems require predictive models to be not only accurate but also comprehensible. Comprehensibility enables human inspection and understanding of the model, making it possible to trace why individual predictions are made. Since most high-accuracy techniques produce opaque models, accuracy is, in practice, regularly sacrificed for comprehensibility. One frequently studied technique, often able to reduce this accuracy vs. comprehensibility tradeoff, is rule extraction, i.e., the activity where another, transparent, model is generated from the opaque. In this paper, it is argued that techniques producing transparent models, either directly from the dataset, or from an opaque model, could benefit from using an oracle guide. In the experiments, genetic programming is used to evolve decision trees, and a neural network ensemble is used as the oracle guide. More specifically, the datasets used by the genetic programming when evolving the decision trees, consist of severa...
Ulf Johansson, Lars Niklasson
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where CIDM
Authors Ulf Johansson, Lars Niklasson
Comments (0)
books