sits_pred_normalize function

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.

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)

Returns

A data.frame with normalized predictor values

Note

Please refer to the sits documentation available in https://e-sensing.github.io/sitsbook/ for detailed examples.

Examples

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

Author(s)

Gilberto Camara, gilberto.camara@inpe.br