Created by W.Langdon from gp-bibliography.bib Revision:1.5433
This white paper reports on the result of a multi-year study of the performance of Discipulus by Science Applications International Corp (SAIC) and RML Technologies, Inc. This study compared Discipulus to several other powerful modelling tools on a wide variety of industrial problems including regression and classification problems, CRM problems, time series problems, complex signal discrimination problems and others.
We compared the modeling capability of Discipulus to the following competitive modelling technologies:
Vapnick Statistical Learning,
Decision Trees, and
In brief summary, the other modelling tools performed inconsistently sometimes they produced very good results and sometimes mediocre or even very poor results. None of these tools produced high quality results across the board. In contrast, Discipulus (at its default settings) always produced results that were the same as or better than the best results from other modelling techniques.
The results described in this white paper have all been previously published in peer-reviewed scientific publications.",
Genetic Programming entries for Larry M Deschaine Frank D Francone