sym.svm: Symbolic Support Vector Machines Regression

Description

Symbolic Support Vector Machines Regression

Usage

sym.svm(
  formula,
  sym.data,
  method = c("cm", "crm"),
  scale = TRUE,
  kernel = "radial"
)

Arguments

formula: a symbolic description of the model to be fit.
sym.data: symbolic data.table
method: method
scale: A logical vector indicating the variables to be scaled. If scale is of length 1, the value is recycled as many times as needed. Per default, data are scaled internally (both x and y variables) to zero mean and unit variance. The center and scale values are returned and used for later predictions.
kernel: the kernel used in training and predicting. You might consider changing some of the following parameters, depending on the kernel type.

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