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rgp (version 0.4-1)

R genetic programming framework

Description

RGP is a simple modular Genetic Programming (GP) system build in pure R. In addition to general GP tasks, the system supports Symbolic Regression by GP through the familiar R model formula interface. GP individuals are represented as R expressions, an (optional) type system enables domain-specific function sets containing functions of diverse domain- and range types. A basic set of genetic operators for variation (mutation and crossover) and selection is provided.

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Version

Install

install.packages('rgp')

Monthly Downloads

96

Version

0.4-1

License

GPL-2

Maintainer

Last Published

August 8th, 2014

Functions in rgp (0.4-1)

exprShapesOfDepth

Upper bounds for expression tree search space sizes

Support for GP buidling blocks

Normalized mean squared error (NMSE)

multiNicheSymbolicRegression

Symbolic regression via multi-niche standard genetic programming

Functions for handling R symbols / names

arithmeticFunctionSet

Default function- and constant factory sets for Genetic Programming

Visualization of functions and expressions as trees

Random crossover (recombination) of functions and expressions

Embed columns in a data frame

Show an overlayed plot of multiple functions

A dist function that supports custom metrics

extractAttributes

Extract a given attribute of all objects in a list and tag that list with the list of extracted attributes

Check if an object is an sType

Repeatedly apply a function

makeCommaEvolutionStrategySearchHeuristic

Comma Evolution Strategy Search Heuristic for RGP

R version of Scaled sum squared error (sSSE)

Create a new R closure given a function body expression and an argument list

Create a new function stub

makeFunctionFitnessFunction

Create a fitness function from a reference function of one variable

Creates an R expression by random growth

commonSubexpressions

Similarity and Distance Measures for R Functions and Expressions

Functions for Lisp-like list processing

Create a new function argument list from a list or vector of strings

buildingBlockTag

Building block tags

makeNaryFunctionFitnessFunction

Create a fitness function from a n-ary reference function

The RGP package

Return the "label" at the Root Node of an Expression Tree

exprToPlotmathExpr

Convert any expression to an expression that is plottable by plotmath

Calculate the fitness value of each individual in a population

Determine the number of arguments of a function

makeStepsStopCondition

Evolution stop conditions

predict.symbolicRegressionModel

Predict method for symbolic regression models

inputVariablesOfIndividual

Functions for analysing GP individuals

orderByParetoCrowdingDistance

Rearrange points via Pareto-based rankings

Coefficient of determination (R^2)

makeArchiveBasedParetoTournamentSearchHeuristic

Archive-based Pareto Tournament Search Heuristic for RGP

Prints a sType and returns it invisible.

makeTournamentSelection

GP selection functions

Splitting and grouping of lists

makeRegressionFitnessFunction

Create a fitness function for symbolic regression

R version of Sum squared error (SSE)

orderByParetoMeasure

Rearrange points via an arbitrary Pareto-based ranking

Breeding of GP individuals

dataDrivenGeneticProgramming

Data-driven untyped standard genetic programming

plotPopulationFitnessComplexity

Fitness/Complexity plot for populations

makeHierarchicalClusterFunction

Clustering Populations for Niching

Complexity measures for R functions and expressions

Plot a 2D function as a 3D surface

MapExpressionNodes

Common higher-order functions for transforming R expressions

Functions for defining the search space for Genetic Programming

makeTinyGpSearchHeuristic

Tiny GP Search Heuristic for RGP

Creates a well-typed R function with a random expression as its body

R version of Mean absolute error (MAE)

Inference of sTypes

summary.geneticProgrammingResult

Summary reports of genetic programming run result objects

Tabulate a list of functions or input variables by their sTypes

Mean squared error (MSE)

latinHypercubeDesign

Create a latin hypercube design (LHD)

Select a continuous subframe of a data frame

Select random childs or subtrees of an expression

multiNicheGeneticProgramming

Cluster-based multi-niche genetic programming

Symbolic squared error (SE)

Sort a vector or list by the result of applying a function

Sum squared error (SSE)

Some simple arithmetic and logic functions for use in GP expressions

randexprTypedGrow

Creates an R expression by random growth respecting type constraints

Functions for decomposing and recombining R expressions

symbolicRegression

Symbolic regression via untyped standard genetic programming

randterminalTyped

Create a random terminal node

Normalize a vector into the interval [0, 1]

exprChildrenOrEmptyList

Return the Children of an Expression or the Empty List if there are None

paretoFrontKneeIndex

Find the knee of a two dimensional pareto front

functionVariablePresenceMap

Variable Presence Maps

Choose a random element from a list or vector

Random mutation of functions and expressions

Creates an R function with a random expression as its body

rangeTypeOfType

Return the range type if t is a function type, otherwise just return t

Utility functions for testing and benchmarking the RGP system

Join elite lists

makeEmptyRestartCondition

Evolution restart conditions

Scaled mean squared error (SMSE)

Mean absolute error (MAE)

makeSeSymbolicFitnessFunction

Create a fitness function based on symbolic squared error (SE)

plotParetoFront

Plot a GP Pareto Front

makeAgeFitnessComplexityParetoGpSearchHeuristic

Age Fitness Complexity Pareto GP Search Heuristic for RGP

Classes for populations of individuals represented as functions

Tabulate a list of functions or input variables by the range part of their sTypes

Sort a vector or list via a given ranking

funcToPlotmathExpr

Convert a function to an expression plottable by plotmath

integerToLogicals

Tools for manipulating boolean functions

geneticProgramming

Standard typed and untyped genetic programming

Create a regular grid design matrix

Type constructors for types in the Rsymbolic type system

Scaled sum squared error (sSSE)

do.call.ignore.unused.arguments

A variant of do.call that ignores unused arguments

Sorting algorithms for vectors and lists

nondeterministicRanking

Create a nondeterministic ranking

tabulateFunction

Tabulate an n-ary function

seSymbolicFunction

Symbolic squared error function (SE)

makeLocalRestartStrategy

Evolution restart strategies

arity.primitive

Determine the number of arguments of a primitive function

Format time and data values into human-readable character vectors

inversePermutation

Calculate the inverse of a permutation

normalizedDesign

Create a normalized design matrix

Root mean squared error (RMSE)