What is the best activation function for classification tasks?

What is the best activation function for classification tasks?

The best activation function for classification tasks often depends on the specific problem. For binary classification, the sigmoid function is commonly used, while softmax is preferred for multi-class classification.

Can you explain why softmax is used for multi-class classification?

Sure! Softmax converts the raw output scores into probabilities that sum to 1, making it suitable for multi-class problems where you want to predict the probability of each class.

Are there any other activation functions I should consider?

Yes, besides sigmoid and softmax, you might also consider ReLU (Rectified Linear Unit) for hidden layers, as it helps with gradient flow.

What about using activation functions in deep learning models?

In deep learning, activation functions like ReLU, Leaky ReLU, and tanh are often used in hidden layers to introduce non-linearity, which helps the model learn complex patterns.