sits_formula_logref function

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) }

Author(s)

Alexandre Ywata de Carvalho, alexandre.ywata@ipea.gov.br

Rolf Simoes, rolf.simoes@inpe.br