Keywords
Computer scienceSelection (genetic algorithm)Factory (object-oriented programming)Inductive logic programmingMachine learningModel selectionArtificial intelligenceMathematical optimizationIndustrial engineeringMathematicsProgramming language
Affiliated Institutions
Related Publications
A general approach for developing system‐specific functions to score protein–ligand docked complexes using support vector inductive logic programming
Abstract Despite the increased recent use of protein–ligand and protein–protein docking in the drug discovery process due to the increases in computational power, the difficulty...
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
Collinearity refers to the non independence of predictor variables, usually in a regression‐type analysis. It is a common feature of any descriptive ecological data set and can ...
jModelTest: Phylogenetic Model Averaging
jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" (Guindon and Gascuel 2003. A simple, fast, and accurate algorithm...
Handbook of Genetic Algorithms
This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems. The first objective is tackled by the editor, Lawrence Davis. Th...
Publication Info
- Year
- 2010
- Type
- book-chapter
- Pages
- 217-225
- Citations
- 13
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
13
OpenAlex
Cite This
Ashwin Srinivasan,
Ganesh Ramakrishnan
(2010).
Parameter Screening and Optimisation for ILP Using Designed Experiments.
Lecture notes in computer science
, 217-225.
https://doi.org/10.1007/978-3-642-13840-9_21
Identifiers
- DOI
- 10.1007/978-3-642-13840-9_21