@@ -98,20 +98,20 @@ def make_model(n_features):
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model = Sequential ()
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model .add (Dense (200 , input_shape = (n_features ,),
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kernel_initializer = 'glorot_normal' ))
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- model .add (Activation ('relu' ))
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model .add (BatchNormalization ())
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- model .add (Dropout (0.5 ))
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- model .add (Dense (100 , kernel_initializer = 'glorot_normal' ))
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model .add (Activation ('relu' ))
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+ model .add (Dropout (0.5 ))
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+ model .add (Dense (100 , kernel_initializer = 'glorot_normal' , use_bias = False ))
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model .add (BatchNormalization ())
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- model .add (Dropout (0.25 ))
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- model .add (Dense (50 , kernel_initializer = 'glorot_normal' ))
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model .add (Activation ('relu' ))
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+ model .add (Dropout (0.25 ))
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+ model .add (Dense (50 , kernel_initializer = 'glorot_normal' , use_bias = False ))
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model .add (BatchNormalization ())
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- model .add (Dropout (0.15 ))
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- model .add (Dense (25 , kernel_initializer = 'glorot_normal' ))
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model .add (Activation ('relu' ))
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+ model .add (Dropout (0.15 ))
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+ model .add (Dense (25 , kernel_initializer = 'glorot_normal' , use_bias = False ))
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model .add (BatchNormalization ())
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+ model .add (Activation ('relu' ))
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model .add (Dropout (0.1 ))
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model .add (Dense (1 , activation = 'sigmoid' ))
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