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