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[ENH] Add and Validate n_layers, n_units, activation & dropout_rate kwargs to MLPNetwork #2338

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[ENH] Add and Validate n_layers, n_units, activation & dropout_rate kwargs to MLPNetwork #2338

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db82312
parametrize MLP
aadya940 Nov 11, 2024
a88c501
minor
aadya940 Nov 11, 2024
57a13fe
minor changes
aadya940 Nov 18, 2024
795f647
some fixes:
aadya940 Nov 18, 2024
4d03300
Merge branch 'main' into mlp-parametrize
aadya940 Nov 18, 2024
61bf5e2
update corresponding classifiers and regressors
aadya940 Nov 18, 2024
ba6d4c0
Automatic `pre-commit` fixes
aadya940 Nov 18, 2024
d470258
fixes
aadya940 Nov 18, 2024
f2b9903
Merge branch 'mlp-parametrize' of https://github.com/aadya940/aeon in…
aadya940 Nov 18, 2024
7eb7d9d
fixes:
aadya940 Nov 18, 2024
78b245a
bug fix
aadya940 Nov 19, 2024
c3733fe
bug fixes
aadya940 Nov 19, 2024
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fixes
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@aadya940
aadya940 committed Nov 18, 2024
commit d47025816157ed08c25008192d19b1a81a376b60
15 changes: 5 additions & 10 deletions aeon/classification/deep_learning/_mlp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -87,10 +87,6 @@ class MLPClassifier(BaseDeepClassifier):
a single string metric is provided, it will be
used as the only metric. If a list of metrics are
provided, all will be used for evaluation.
activation : string or a tf callable, default="sigmoid"
Activation function used in the output linear layer.
List of available activation functions:
https://keras.io/api/layers/activations/

Notes
-----
Expand All @@ -115,11 +111,11 @@ class MLPClassifier(BaseDeepClassifier):

def __init__(
self,
n_layers = 3,
n_units = 200,
activation = "relu",
dropout_rate = None,
dropout_last = None,
n_layers=3,
n_units=200,
activation="relu",
dropout_rate=None,
dropout_last=None,
use_bias=True,
n_epochs=2000,
batch_size=16,
Expand Down Expand Up @@ -150,7 +146,6 @@ def __init__(
self.loss = loss
self.metrics = metrics
self.use_mini_batch_size = use_mini_batch_size
self.activation = activation
self.use_bias = use_bias
self.file_path = file_path
self.save_best_model = save_best_model
Expand Down
16 changes: 5 additions & 11 deletions aeon/regression/deep_learning/_mlp.py
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Expand Up @@ -83,10 +83,6 @@ class MLPRegressor(BaseDeepRegressor):
by `np.random`.
Seeded random number generation can only be guaranteed on CPU processing,
GPU processing will be non-deterministic.
activation : string or a tf callable, default="relu"
Activation function used in the output linear layer.
List of available activation functions:
https://keras.io/api/layers/activations/
output_activation : str = "linear"
Activation for the last layer in a Regressor.
optimizer : keras.optimizer, default = tf.keras.optimizers.Adam()
Expand All @@ -111,11 +107,11 @@ class MLPRegressor(BaseDeepRegressor):

def __init__(
self,
n_layers = 3,
n_units = 200,
activation = "relu",
dropout_rate = None,
dropout_last = None,
n_layers=3,
n_units=200,
activation="relu",
dropout_rate=None,
dropout_last=None,
use_bias=True,
n_epochs=2000,
batch_size=16,
Expand All @@ -131,7 +127,6 @@ def __init__(
last_file_name="last_model",
init_file_name="init_model",
random_state=None,
activation="relu",
output_activation="linear",
optimizer=None,
):
Expand All @@ -145,7 +140,6 @@ def __init__(
self.verbose = verbose
self.loss = loss
self.metrics = metrics
self.activation = activation
self.use_bias = use_bias
self.file_path = file_path
self.save_best_model = save_best_model
Expand Down