View source: R/sits_predictors.R
sits_stats | R Documentation |
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 necessary to extract the statistics of each band of the samples. This function computes the 2 of the distribution of each band of the samples. This values are used as minimum and maximum values in the normalization operation performed by the sits_pred_normalize() function.
sits_stats(samples)
samples |
Time series samples uses as training data. |
A list with the 2 training data.
Please refer to the sits documentation available in <https://e-sensing.github.io/sitsbook/> for detailed examples.
Gilberto Camara, gilberto.camara@inpe.br
if (sits_run_examples()) {
stats <- sits_stats(samples_modis_ndvi)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.