February 2, 2012

Paper: Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process - EUROCAST 2011

This paper was prepared for the EUROCAST 2011 conference and it basically contains a short summary of the work I have carried out for my Master Thesis Project. Here is the abstract of the article:
This research is focused on reducing the average size of the solutions generated by an enhanced GP process without affecting the high predictive accuracy this method exhibits when being applied on a complex, industry proposed, regression problem. As such, the effects the GP enhancements have on bloat have been studied and, finally, a bloat control system based on dynamic depth limiting (DDL) and iterated tournament pruning (ITP) was designed. The resulting bloat control system is able to improve by approx. 40% the average GP solution parsimony without impacting average solution accuracy.
You can download a preliminary version of the paper by clicking here or from my Downloads box (Improving the Parsimony of Regression Models for an Enhanced GP Process - EUROCAST 2011.pdf). The same preliminary draft of the document can be previewed at the bottom of this post. The original publication is available at www.springerlink.com.

For citations please use the following BibTeX reference:

  author = {Alexandru-Ciprian Z\u{a}voianu and Gabriel Kronberger and Michael Kommenda and Daniela Zaharie and Michael Affenzeller},
  title = {Improving the Parsimony of Regression Models for an Enhanced Genetic Programming Process},
  booktitle = {Computer Aided Systems Theory - EUROCAST 2011},
  publisher = {Springer Berlin / Heidelberg},
  year = {2012},
  editor = {Moreno-Diaz, Roberto and Pichler, Franz and Quesada-Arencibia, Alexis},
  volume = {6927},
  series = {Lecture Notes in Computer Science},
  pages = {264-271},
  doi = {10.1007/978-3-642-27549-4_34},

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