sits_formula_logref: Define a loglinear formula for classification models

In sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes

Define a loglinear formula for classification models

Description

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.

Usage

sits_formula_logref(predictors_index = -2:0)

Arguments

predictors_index

Index of the valid columns to compose formula (default: -2:0).

Value

A function that computes a valid formula using a log function.

Author(s)

Alexandre Ywata de Carvalho, [e-mail]

Rolf Simoes, [e-mail]

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)
}

sits documentation built on Sept. 11, 2024, 6:36 p.m.