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[ENH] The Default value for use_mini_batch_size should be set to False #1065

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Jan 18, 2024
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[ENH] The Default value for use_mini_batch_size should be set to False #1065

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4 changes: 2 additions & 2 deletions aeon/classification/deep_learning/_fcn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@ class FCNClassifier(BaseDeepClassifier):
The number of epochs to train the model.
batch_size : int, default = 16
The number of samples per gradient update.
use_mini_batch_size : bool, default = True
use_mini_batch_size : bool, default = False
Whether or not to use the mini batch size formula.
random_state : int or None, default = None
Seed for random number generation.
Expand Down Expand Up @@ -117,7 +117,7 @@ def __init__(
last_file_name="last_model",
n_epochs=2000,
batch_size=16,
use_mini_batch_size=True,
use_mini_batch_size=False,
callbacks=None,
verbose=False,
loss="categorical_crossentropy",
Expand Down
4 changes: 2 additions & 2 deletions aeon/regression/deep_learning/_fcn.py
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Expand Up @@ -42,7 +42,7 @@ class FCNRegressor(BaseDeepRegressor):
the number of epochs to train the model
batch_size : int, default = 16
the number of samples per gradient update.
use_mini_batch_size : bool, default = True,
use_mini_batch_size : bool, default = False,
whether or not to use the mini batch size formula
random_state : int or None, default=None
Seed for random number generation.
Expand Down Expand Up @@ -120,7 +120,7 @@ def __init__(
last_file_name="last_model",
n_epochs=2000,
batch_size=16,
use_mini_batch_size=True,
use_mini_batch_size=False,
callbacks=None,
verbose=False,
output_activation="linear",
Expand Down