I am new to GluonTS and I am trying to understand how the concept works. On the documentation website, under the section "Splitting datasets into training and test"
they define a mechanism to split the train and test data as follows:
training_dataset, test_template = split(
dataset, date=pd.Period("2015-04-07 00:00:00", freq="1H")
)
test_pairs = test_template.generate_instances(
prediction_length=prediction_length,
windows=3,
distance=24,
)
training_dataset can be used directly as follows:
predictor = estimator.train(training_dataset)
The type of this test_pairs is gluonts.dataset.split.TestData
but when using test_pairs as input for forecasting:
forecast_it, ts_it = make_evaluation_predictions(
dataset=test_pairs, predictor=predictor,
num_samples=100,
)
The type for ts_it will be a "map" and when converting it to a list it will return an empty list.
Does anyone know how to use the test_pairs for actually making predictions and evaluating the results?
