Name
Title | ||
|---|---|---|
Statistical distribution of generation-to-success in GP: application to model accumulated success probability |
Abstract | ||
|---|---|---|
Many different metrics have been defined in Genetic Programming. Depending on the experiment requirements and objectives, a collection of measures are selected in order to achieve an understanding of the algorithm behaviour. One of the most common metrics is the accumulated success probability, which evaluates the probability of an algorithm to achieve a solution in a certain generation. We propose a model of accumulated success probability composed by two parts, a binomial distribution that models the total number of success, and a lognormal approximation to the generation-to-success, that models the variation of the success probability with the generation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-20407-4_14 | EuroGP |
Keywords | Field | DocType |
statistical distribution,different metrics,genetic programming,binomial distribution,total number,certain generation,success probability,experiment requirement,common metrics,lognormal approximation,algorithm behaviour,probability measure,measures | Binomial distribution,Applied probability,Joint probability distribution,Computer science,Multinomial distribution,Posterior probability,Empirical probability,Probability distribution,Mathematical statistics,Artificial intelligence,Statistics,Machine learning | Conference |
Volume | ISSN | Citations |
6621 | 0302-9743 | 8 |
PageRank | References | Authors |
0.56 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David F. Barrero | 1 | 120 | 17.17 |
| Bonifacio Castaño | 2 | 19 | 5.10 |
| María D. R-Moreno | 3 | 97 | 15.22 |
| David Camacho | 4 | 331 | 43.45 |