sym.predict.symbolic_gbm_cm: Predict model_gbm_cm model

In RSDA: R to Symbolic Data Analysis

Predict model_gbm_cm model

Description

Predict model_gbm_cm model

Usage

## S3 method for class 'symbolic_gbm_cm'
sym.predict(model, new.sym.data, n.trees = 500, ...)

Arguments

model	model
new.sym.data	new data
n.trees	Integer specifying the total number of trees to fit. This is equivalent to the number of iterations and the number of basis functions in the additive expansion. Default is 100.
...	optional parameters

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

RSDA documentation built on Nov. 10, 2023, 5:06 p.m.