Normalize predictor values

Most machine learning algorithms require data to be normalized. This applies to the "SVM" method and to all deep learning ones. To normalize the predictors, it is required that the statistics per band for each sample have been obtained by the "sits_stats" function.

Usage

sits_pred_normalize(pred, stats)

Arguments

pred

X-Y predictors: a data.frame with one row per sample.

stats

Values of time series for Q02 and Q98 of the data (list of numeric values with two elements)

Value

A data.frame with normalized predictor values

Author

Gilberto Camara, gilberto.camara@inpe.br

Examples

if (sits_run_examples()) {
    stats <- sits_stats(samples_modis_ndvi)
    pred <- sits_predictors(samples_modis_ndvi)
    pred_norm <- sits_pred_normalize(pred, stats)
}