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[ENH] Added TCN forecaster in aeon/forecasting/deep_learning #2938
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class TCNForecaster(BaseDeepForecaster, DirectForecastingMixin): | ||
"""A deep learning forecaster using Temporal Convolutional Network (TCN). | ||
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It leverages the `TCNNetwork` from aeon's network module |
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parameters missing are:
save_last_model, save_init_model and best_model_name and init_model_name, please check any example in aeon/classification/deep_learning to see how to use them
model = tf.keras.Model(inputs=input_layer, outputs=output) | ||
return model | ||
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def _fit(self, y, exog=None): |
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Please take a look at this example from deep classification in aeon to see how to handle saving best last and init model, and their names, please do the exact same thing, especially the loading of the best model at the end where we do try and except:
def _fit(self, X, y): |
Reference Issues/PRs
Fixes #2937.
What does this implement/fix? Explain your changes.
Adds TCNForecaster in aeon/toolkit.
Does your contribution introduce a new dependency? If yes, which one?
Any other comments?
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