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GAparsimony (version 0.9.5)

Searching Parsimony Models with Genetic Algorithms

Description

Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) . To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.

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Version

Install

install.packages('GAparsimony')

Monthly Downloads

222

Version

0.9.5

License

GPL (>= 2)

Issues

1

Pull Requests

0

Stars

6

Forks

3

Maintainer

F.J. Martinez-de-Pison

Last Published

April 7th, 2023

Functions in GAparsimony (0.9.5)

GA-internal

Internal GA functions
parsimony_Population

Population initialization in GA-PARSIMONY with a combined chromosome of model parameters and selected features
parsimony_Selection

Selection operators in GA-PARSIMONY
parsimony_crossover

Crossover operators in GA-PARSIMONY
numericOrNA-class

Virtual Class "numericOrNA" - Simple Class for subassignment Values
ga_parsimony

GA-PARSIMONY
parsimony_importance

Percentage of appearance of each feature in elitist population
parsimony_rerank

Function for reranking by complexity in parsimonious model selection process
ga_parsimony-class

Class "ga_parsimony"
parsimony_monitor

Functions for monitoring GA-PARSIMONY algorithm evolution
summary.ga_parsimony-method

Summary for GA-PARSIMONY
plot.ga_parsimony-method

Plot of GA evolution of elitists
matrixNULL-class

Virtual Class "matrixNULL" - Simple Class for matrix or NULL
GAparsimony-package

GAparsimony
parsimony_Mutation

Mutation operators in GA-PARSIMONY