diff --git a/toolkit.py b/toolkit.py
index c311170e587cd44b99b97a3f53c1079dbaff1ae3..0f804b774afe24279e337a27fb0f803d8653395a 100755
--- a/toolkit.py
+++ b/toolkit.py
@@ -38,6 +38,7 @@ from keras.models import Sequential, Model, model_from_json
 from keras.layers import Dense, Dropout, Input, Masking, GRU, LSTM, concatenate, SimpleRNN
 from keras.callbacks import History, EarlyStopping, CSVLogger, ModelCheckpoint, TensorBoard
 from keras.optimizers import SGD
+from keras.activations import relu
 import keras.initializers
 import keras.optimizers
 from keras.utils.vis_utils import model_to_dot
@@ -161,6 +162,8 @@ class ClassificationProject(object):
 
     :param activation_function_output: activation function in the output layer
 
+    :param leaky_relu_alpha: set this to a non-zero value to use the LeakyReLU variant with a slope in the negative part
+
     :param out_dir: base directory in which the project directories should be stored
 
     :param scaler_type: sklearn scaler class name to transform the data before training (options: "StandardScaler", "RobustScaler")
@@ -269,6 +272,7 @@ class ClassificationProject(object):
                         kfold_splits=None,
                         kfold_index=0,
                         activation_function='relu',
+                        leaky_relu_alpha=None,
                         activation_function_output='sigmoid',
                         scaler_type="WeightedRobustScaler",
                         step_signal=2,
@@ -344,6 +348,9 @@ class ClassificationProject(object):
         self.kfold_splits = kfold_splits
         self.kfold_index = kfold_index
         self.activation_function = activation_function
+        self.leaky_relu_alpha = leaky_relu_alpha
+        if self.activation_function == "relu" and self.leaky_relu_alpha:
+            self.activation_function = lambda x : relu(x, alpha=self.leaky_relu_alpha)
         self.activation_function_output = activation_function_output
         self.scaler_type = scaler_type
         self.step_signal = step_signal
@@ -805,6 +812,7 @@ class ClassificationProject(object):
 
         if self._model is None:
 
+
             # input
             input_layer = Input((len(self.fields),))