sym.rf: Symbolic Regression with Random Forest

In PROMiDAT/RSDA: R to Symbolic Data Analysis

Symbolic Regression with Random Forest

Description

Symbolic Regression with Random Forest

Usage

sym.rf(formula, sym.data, method = c("cm", "crm"), ntree = 500)

Arguments

formula	a formula, with a response but no interaction terms. If this a a data frame, that is taken as the model frame (see model.frame).
sym.data	symbolic data table
method	cm crm
ntree	Number of trees to grow. This should not be set to too small a number, to ensure that every input row gets predicted at least a few times.

References

Lima-Neto, E.A., De Carvalho, F.A.T., (2008). Centre and range method to fitting a linear regression model on symbolic interval data. Computational Statistics and Data Analysis52, 1500-1515

Lima-Neto, E.A., De Carvalho, F.A.T., (2010). Constrained linear regression models for symbolic interval-valued variables. Computational Statistics and Data Analysis 54, 333-347

Lima Neto, E.d.A., de Carvalho, F.d.A.T. Nonlinear regression applied to interval-valued data. Pattern Anal Applic 20, 809–824 (2017). https://doi.org/10.1007/s10044-016-0538-y

Rodriguez, O. (2018). Shrinkage linear regression for symbolic interval-valued variables.Journal MODULAD 2018, vol. Modulad 45, pp.19-38

PROMiDAT/RSDA documentation built on Sept. 14, 2023, 9:16 p.m.