In typical supervised learning, class labels of data (e.g. observations) are predefined. Decision on unlabelled data is usually made after learning a classifier using available training samples. Examples of supervised classifiers include Support Vector Machines (SVM) and Artificial Neural Network (ANN).

What are classes in supervised learning?

In machine learning, classification is a supervised learning concept which basically categorizes a set of data into classes. The most common classification problems are – speech recognition, face detection, handwriting recognition, document classification, etc.

What is supervised in supervised learning?

The majority of practical machine learning uses supervised learning. Supervised learning is where you have input variables (x) and an output variable (Y) and you use an algorithm to learn the mapping function from the input to the output.