bm_svr: Fit Support Vector Regression models

In vcerqueira/tsensembler: Dynamic Ensembles for Time Series Forecasting

Description

Learning a Support Vector Regression model from training data.

Usage

bm_svr(form, data, lpars)

Arguments

form	formula
data	training data for building the predictive model
lpars	a list containing the learning parameters

Details

Parameter setting can vary in kernel, C, and epsilon parameters.

See ksvm for a comprehensive description.

Imports learning procedure from kernlab package.

See Also

other learning models: bm_mars; bm_ppr; bm_gbm; bm_glm; bm_cubist; bm_randomforest; bm_pls_pcr; bm_ffnn; bm_gaussianprocess

Other base learning models: bm_cubist, bm_ffnn, bm_gaussianprocess, bm_gbm, bm_glm, bm_mars, bm_pls_pcr, bm_ppr, bm_randomforest

vcerqueira/tsensembler documentation built on Oct. 28, 2020, 11:46 p.m.