UNIK4590 – Pattern Recognition
Schedule, syllabus and examination date
Bayesian decision theory, supervised learning, parametric and non-parametric methods, linear discriminant functions, feature extraction, unsupervised learning, cluster analysis, syntactic methods.
The course is an introduction to classification theory and pattern recognition. The students are provided with sufficient knowledge for designing and evaluating classifiers using proper methods for the problem at hand.
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Formal prerequisite knowledge
Recommended previous knowledge
STK4030 "Modern Data Analysis"http://www.uio.no/studier/emner/matnat/math/STK4030/, 8 credits.
UNIKI385, 8 credits.
3 hrs. lectures and exercises per week. There will be mandatory assignments that need to be approved in order to attend the exam.
Oral exam at the end of the semester. In case of many students, there may be held a written exam.
In order to take the exam, mandatory assignments needs to be approved.
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Explanations and appeals
Resit an examination
Students who can document a valid reason for absence from the regular examination are offered a postponed examination at the beginning of the next semester.
Re-scheduled examinations are not offered to students who withdraw during, or did not pass the original examination.