About this question
What could be the scenarios where I might opt for a Leaky ReLU activation function instead of choosing the Traditional ReLU function in the whole context of neural network designing by using the Keras?
What could be the scenarios where I might opt for a Leaky ReLU activation function instead of choosing the Traditional ReLU function in the whole context of neural network designing by using the Keras?
Log in to share your answer and help other learners.
Log in to answerBest Answer · By JanBask Data Science Expert
Answered on Dec 6, 2023
In the context of neural networks, if you choose Leaky ReLu Keras over traditional ReLu function, then it becomes crucial to consider combating the “dyingReLU problem. This particular issue arises in the scenario where ReLU becomes inactive or it always shows zero as the conclusion and even fails to learn during training. To solve this particular issue the ReLU can help you address this as it allows a small, non-zero gradient for the negative inputs which can lead to preventing the neurons from becoming entirely dormant.
Moreover, if you provide a slight slope for the negative inputs, then Leaky ReLU will promote more robust and strong diverse learning. It will further reduce the unresponsiveness risk of neurons.
Therefore, in the scenarios where the dead neurons are there because of negative inputs the Leaky ReLU can be beneficial in preventing stagnation.
Join our data science certification course online for more conceptual topics like this.