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FIX: move the BatchNormalization before the activation with no bias #531

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Merged
merged 1 commit into from
Jan 19, 2019
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FIX: move the BatchNormalization before the activation with no bias #531

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9 changes: 9 additions & 0 deletions doc/whats_new/v0.5.rst
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Expand Up @@ -22,3 +22,12 @@ Maintenance

- Make it possible to ``import imblearn`` and access submodule.
:issue:`500` by :user:`Guillaume Lemaitre <glemaitre>`.

Bug
...

- Fix wrong usage of :class:`keras.layers.BatchNormalization` in
``porto_seguro_keras_under_sampling.py`` example. The batch normalization
was moved before the activation function and the bias was removed from the
dense layer.
:issue:`531` by :user:`Guillaume Lemaitre <glemaitre>`.
14 changes: 7 additions & 7 deletions examples/applications/porto_seguro_keras_under_sampling.py
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Expand Up @@ -98,20 +98,20 @@ def make_model(n_features):
model = Sequential()
model.add(Dense(200, input_shape=(n_features,),
kernel_initializer='glorot_normal'))
model.add(Activation('relu'))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Dense(100, kernel_initializer='glorot_normal'))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(100, kernel_initializer='glorot_normal', use_bias=False))
model.add(BatchNormalization())
model.add(Dropout(0.25))
model.add(Dense(50, kernel_initializer='glorot_normal'))
model.add(Activation('relu'))
model.add(Dropout(0.25))
model.add(Dense(50, kernel_initializer='glorot_normal', use_bias=False))
model.add(BatchNormalization())
model.add(Dropout(0.15))
model.add(Dense(25, kernel_initializer='glorot_normal'))
model.add(Activation('relu'))
model.add(Dropout(0.15))
model.add(Dense(25, kernel_initializer='glorot_normal', use_bias=False))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(Dropout(0.1))
model.add(Dense(1, activation='sigmoid'))

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