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55 review models architecture #75
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…at it can perform fit and predict and perform multivariate prediction even when the model is univariate.
…model class as well as model class instance. Update data module and dataset creation with torch. Update docs accordingly.
…his allows to ensure that evaluation pipeline is common to all models. Still, model must ensure to be able to process batch of data for inference (predict method).
…ata (a list of time series for now). It has been implemented for all models except scikit-learn compatible ones. Update documentation accordingly, and update dependencies.
…g holder. Refactor and clean some of the code.
…s and make some modification in model config class to pass dynamic parameters
…fixes in some modules. Benchmark is now running succesfully and we get the expected results.
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Great work
@@ -1,6 +1,6 @@ | |||
from .detection import detectors, abstract_detector | |||
from .generation import generators, abstract_generator | |||
from .modelling import Model, models, abstract_model | |||
from .modelling import Model, model_interface, models |
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change to abstract_model
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updated in new commit
# Darts Models | ||
self.model = DartsForecastingModel(self.model, **self.params) | ||
# This take all the sklearn regressors and pipelines | ||
elif issubclass(self.model, BaseEstimator): | ||
elif is_subclass_or_instance_of_subclass(self.model, BaseEstimator): | ||
if size_of_ts > 1: |
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Make an issue to group the SkForecaster classes here so that the if
isn't imbricated.
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done (#78)
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I now approved
In this PR, model architecture was improved. Specifically, this was done :