5 ECTS cr
|Language of instruction
English. Examination can be taken in English or Finnish.
The course unit is held in the spring semester, during period III. It is recommended to complete the course at the end of studies.
After completing the course, student
1. can design simple optimal classifiers from the basic theory and assess their performance.
2. can explain the Bayesian decision theory and apply it to derive minimum error classifiers and minimum cost classifiers.
3. can apply the basics of gradient search method to design a linear discriminant function.
4. can apply regression techniques to practical machine learning problems.
Introduction. Bayesian decision theory. Discriminant functions. Parametric and non-parametric classification. Feature extraction. Classifier design. Example classifiers. Statistical regression methods.
|Mode of delivery
Face-to-face teaching, guided laboratory work and independent assignment.
|Learning activities and teaching methods
Lectures 10h, Laboratory work 20h, Self-study 20h, Independent task assignment, written examination.
Students who are interested in data analysis technology. Students of the University of Oulu.
|Prerequisites and co-requisites
The mathematic studies of the candidate degree program of computer science and engineering, or equivalent. Programming skills, especially basics of the Matlab.
|Recommended optional programme components
The course is an independent entity and does not require additional studies carried out at the same time.
|Recommended or required reading
Duda RO, Hart PE, Stork DG, Pattern classification, John Wiley & Sons Inc., 2nd edition, 2001. Handouts.
|Assessment methods and criteria
Laboratory work is supervised by assistants who also check that the task assignments are completed properly. The independent task assignment is graded. The course ends with a written exam.
Read more about assessment criteria at the University of Oulu webpage.
The course unit utilizes a numerical grading scale 1-5. In the numerical scale zero stands for a fail. The final grade is established by weighing the written exam by 2/3 and the task assignment by 1/3.
|Working life cooperation