R: Symbolic Regression Framework

# Symbolic Regression Framework

## Documentation for package ‘symbolicr’ version 1.0.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

analyze.variables | Analyze Variables Get information on the relative importance of each variable included in your formula.
comb.search | Explore given combinations of formula terms
cross.validate | Test a non-linear formula
dataset.min.maxs | Compute dataset column-wise statistics: min, absmin, absmax, projzero
empty.sample | Return an empty data.frame with the columns returned by 'random.search'
exaustive.search | Explore all combinations of formula terms
genetic.search | Genetic Algorithm for non-linear formula optimization
monitor.formula.fun | Default formula to monitor genetic evolution
normalize | Normalize a dataset
normalize.test | Normalize a dataset with pre-defined column mean and standard deviation
parse.vars | Parse text representation of a non-linear formula term
pe.r.squared.formula.len.fitness | Default fitness function for 'genetic.search'
pred.vs.obs | Plot "predicted vs observed" using a given formula
random.search | Random search for non-linear formula optimization
regressors | Compute regressors of a given non-linear formula
regressors.names | Compute all possible formula terms from a given dataset
serialize.vars | Parse text representation of a non-linear formula term
test.formula | Test a non-linear formula, get an aggregated result.
transformations.names | Get transformed regressors names