The concept is a Boolean-valued function defined over a large set of objects or events.

Concept Learning

Concept Learning is defined as inferring a Boolean-valued function from training examples of input and output of the function.

Concept Learning can be represented using -

  • Instance x: It is said to be a collection of attributes.
  • Target function c: For example, X -> [0,1]
  • Hypothesis h: Hypothesis h is a conjunction of constraints on the attributes. A constraint can be a specific value or no value at all.
  • Training example d: An instance x(i) paired with the target function c.