def LocalTabularPredictor(*args, **kwargs) -> Localizer:
"""
A predictor that trains an ad-hoc model for each time series that it is
given to predict.
The constructor arguments are the same as for ``TabularEstimator``.
"""
return Localizer(TabularEstimator(*args, **kwargs))
def test_localizer():
dataset = ListDataset(
data_iter=[{
"start": "2012-01-01",
"target": (np.zeros(20) + i * 0.1 + 0.01),
"id": f"{i}",
} for i in range(3)],
freq="1H",
)
estimator = MeanEstimator(prediction_length=10, freq="1H", num_samples=50)
local_pred = Localizer(estimator=estimator)
agg_metrics, _ = backtest_metrics(test_dataset=dataset,
predictor=local_pred)
def test_localizer():
dataset = ListDataset(
data_iter=[{
'start': '2012-01-01',
'target': (np.zeros(20) + i * 0.1 + 0.01),
'id': f'{i}',
} for i in range(3)],
freq='1H',
)
estimator = MeanEstimator(prediction_length=10, freq='1H', num_samples=50)
local_pred = Localizer(estimator=estimator)
agg_metrics, _ = backtest_metrics(train_dataset=None,
test_dataset=dataset,
forecaster=local_pred)
def LocalTabularPredictor(*args, **kwargs) -> Localizer:
return Localizer(TabularEstimator(*args, **kwargs))