| kgp.tree.ArityException |
Exception given when the number of arguments given to a function does not match its arity. |
| kgp.fitness.BaseMetric |
A base implementation for measuring the fitness of solutions. |
| kgp.evolution.BaseModel |
A base model for evolving trees. |
| kgp.examples.BasicRegressionProblem |
A basic regression problem for KGP to solve. |
| kgp.fitness.Case |
A case in a data set. |
| kgp.fitness.CaseLoader |
A component that can load a set of cases from some source. |
| kgp.fitness.Cases |
A set of cases that a program will be trained on. |
| kgp.tree.Constant |
A terminal node that represents a constant value. |
| kgp.fitness.CsvCaseLoader |
A CaseLoader that loads cases from a CSV file. |
| kgp.fitness.CsvCaseLoaderOptions |
Options to configure a CsvCaseLoader instance. |
| kgp.examples.CustomOperations |
A set of custom operations used by the example problems. |
| kgp.evolution.EvolutionOptions |
A collection of options available to configure evolution by the BaseModel. |
| kgp.fitness.Feature |
A feature of some case in a data set. |
| kgp.fitness.FitnessFunction |
A function that will evaluate the performance a program based on how close its outputs were to the cases given. |
| kgp.fitness.FitnessFunctions |
A collection of standard fitness functions as metrics. |
| kgp.tree.Function |
A node that can perform some function on a set of arguments. |
| kgp.tree.Input |
A terminal node that represents a feature value. |
| kgp.utilities.IntervalSequenceGenerator |
A component that can generate sequences of doubles with a specified interval. |
| kgp.examples.Keijzer6 |
The Keijzer-6 problem as given by White et al. (2013). |
| kgp.examples.Korns12 |
The Korns-12 problem as given by White et al. (2013). |
| kgp.fitness.Metric |
Provides a way of measuring the fitness of a set of outputs. |
| kgp.evolution.Model |
A model that trains a population of solutions. |
| kgp.examples.Nguyen7 |
The Nguyen-7 problem as given by White et al. (2013). |
| kgp.tree.Node |
A node that makes up a program tree. |
| kgp.tree.Nodes |
A collection of function nodes that are available by default. |
| kgp.tree.Operation |
An operation is really just a mapping of arguments to a value. |
| kgp.fitness.Outputs |
A set of outputs given by a program on a set of training cases. |
| kgp.examples.Pagie1 |
The Pagie-1 problem as given by White et al. (2013). |
| kgp.fitness.ParsimonyAwareMetric |
Provides a way of measuring the fitness of a set of outputs with a penalty for parsimony pressure. |
| kgp.examples.QuarticPolynomial |
The quartic polynomial regression problem for KGP to solve. |
| kgp.tree.Terminal |
A node that does not have any child nodes. |
| kgp.evolution.TournamentSelection |
A component that is able to perform tournament selection on a collection of individuals. |
| kgp.tree.Tree |
Represents a program as a tree of nodes. |
| kgp.tree.TreeGenerationMode |
Represents the different types of tree generation methods. |
| kgp.tree.TreeGenerator |
Generates Trees using a given function set and options. |
| kgp.tree.TreeGeneratorOptions |
Options that control tree generation by a TreeGenerator. |
| kgp.utilities.UniformlyDistributedSequenceGenerator |
A component that can generate uniformly distributed sequences of doubles within a specified interval. |
| kgp.examples.Vladislavleva4 |
The Vladislavleva-4 problem as given by White et al. (2013). |