Course content

Bayesian decision theory, supervised learning, parametric and non-parametric methods, linear discriminant functions, feature extraction, unsupervised learning, cluster analysis, syntactic methods.

Learning outcome

After completing the course, you will be able to:

  • describe the field of classification theory and pattern recognition
  • design and evaluating classifiers using proper methods for the problem at hand

Admission

Students admitted at UiO must apply for courses in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.

Nordic citizens and applicants residing in the Nordic countries may apply to take this course as a single course student.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures for international applicants.

Prerequisites

Formal prerequisite knowledge

None.

Recommended previous knowledge

MAT1120 – Linear Algebra MAT1110 – Calculus and Linear Algebra STK1000 – Introduction to Applied Statistics