Introduction to Softmax Classifier in PyTorch
While a logistic regression classifier is used for binary class classification, softmax classifier is a supervised learning algorithm which is mostly used when multiple classes are involved.
Softmax classifier works by assigning a probability distribution to each class. The probability distribution of the class with the highest probability is normalized to 1, and all other probabilities are scaled accordingly.
Similarly, a softmax function transforms the output of neurons into a probability distribution over the classes. It has the following properties:
- It is related to the logistic sigmoid, which is used in probabilistic modeling and has similar properties.
- It takes values between 0 and 1, with 0 corresponding to an impossible event and 1 corresponding to an event that is