Define a loglinear formula for classification models
Define a loglinear formula for classification models
A function to be used as a symbolic description of some fitting models such as svm and random forest. This function tells the models to do a log transformation of the inputs. The predictors_index parameter informs the positions of tb fields corresponding to formula independent variables. If no value is given, the default is NULL, a value indicating that all fields will be used as predictors.
sits_formula_logref(predictors_index =-2:0)
Arguments
predictors_index: Index of the valid columns to compose formula (default: -2:0).
Returns
A function that computes a valid formula using a log function.
Examples
if(sits_run_examples()){# Example of training a model for time series classification# Retrieve the samples for Mato Grosso# train an SVM model ml_model <- sits_train(samples_modis_ndvi, ml_method = sits_svm(formula = sits_formula_logref()))# classify the point point_ndvi <- sits_select(point_mt_6bands, bands ="NDVI")# classify the point point_class <- sits_classify( data = point_ndvi, ml_model = ml_model
) plot(point_class)}