Question

The logistic (or sigmoid) function, as an alternative discriminant, suggests that real data are not likely to be cleanly separable, especially when the number of features we have at our disposal is relatively small. Since the labels are 0 or 1, you could look for a way to interpret labels as probabilities rather than as hard (0 or 1) labels. One such function is the logistic function, also referred to as the logit or sigmoid function.

A) True
B) False

Answer 1

The statement is True. The logistic function is used as an alternative discriminant when handling real data that is not cleanly separable, especially with a small number of features. It allows for interpreting labels as probabilities rather than hard labels.

Step-by-step explanation:

The statement is True.

The logistic (or sigmoid) function is indeed used as an alternative discriminant when dealing with real data that are not likely to be cleanly separable, especially with a relatively small number of features. In this context, the logistic function allows for interpreting labels as probabilities rather than hard (0 or 1) labels. The logistic function, also known as the logit or sigmoid function, maps any real number to a value between 0 and 1, which can be interpreted as a probability.