What is the difference between a classifier and a model?



Model: In machine learning field, the terms hypothesis and model are often used interchangeably. In other sciences, they can have different meanings, i.e., the hypothesis would be the “educated guess” by the scientist, and the model would be the manifestation of this guess that can be used to test the hypothesis.

Classifier: A classifier is a special case of a hypothesis (nowadays, often learned by a machine learning algorithm). A classifier is a hypothesis or discrete-valued function that is used to assign (categorical) class labels to particular data points.

In the email classification example, this classifier could be a hypothesis for labeling emails as spam or non-spam. However, a hypothesis must not necessarily be synonymous to a classifier.

In a different application, our hypothesis could be a function for mapping study time and educational backgrounds of students to their future SAT scores.