103 search results - page 3 / 21 » Selecting the Optimal Rule Set Using a Bacterial Evolutionar... |
GECCO
2009
Springer
13 years 10 months ago
2009
Springer
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
GECCO
2009
Springer
14 years 10 days ago
2009
Springer
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
GECCO
2003
Springer
13 years 11 months ago
2003
Springer
One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their si...
EMO
2009
Springer
13 years 10 months ago
2009
Springer
Abstract. Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal se...