View source: R/sits_predictors.R
sits_pred_sample | R Documentation |
Many machine learning algorithms (especially deep learning) use part of the original samples as test data to adjust its hyperparameters and to find an optimal point of convergence using gradient descent. This function extracts a fraction of the predictors to serve as test values for the deep learning algorithm.
sits_pred_sample(pred, frac)
pred |
X-Y predictors: a data.frame with one row per sample. |
frac |
Fraction of the X-Y predictors to be extracted |
A data.frame with the chosen fraction of the X-Y predictors.
Gilberto Camara, gilberto.camara@inpe.br
if (sits_run_examples()) {
pred <- sits_predictors(samples_modis_ndvi)
pred_frac <- sits_pred_sample(pred, frac = 0.5)
}
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