Which activation function is most likely to be used in the output layer for a multi-class classification problem?

The activation function most likely to be used in the output layer for a multi-class classification problem is the Softmax function.

Here's why:

1. The Softmax function is able to handle multiple classes, which is necessary for a multi-class classification problem.

2. The Softmax function outputs a probability distribution over the target classes. This means that for each input, the Softmax function outputs the probability of that input belonging to each target class.

3. The output of the Softmax function is a vector that sums to 1, which is useful for interpreting the output as probabilities.

4. The class with the highest probability is considered the output class.

So, in a multi-class classification problem, the Softmax function is typically used in the output layer to determine the probabilities of each class and the class with the highest probability is chosen as the output class.