Uncertainty of classification on limited data
Thesis event information
Date and time of the thesis defence
Place of the thesis defence
Linnanmaa L10, https://oulu.zoom.us/j/62679625297
Topic of the dissertation
Uncertainty of classification on limited data
Doctoral candidate
Master of science Tuomo Alasalmi
Faculty and unit
University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Biomimetics and intelligent systems group
Subject of study
Computer science and engineering
Opponent
Professor Henrik Boström, KTH Royal Institute of Technology
Custos
Professor Juha Röning, University of Oulu
Uncertainty of classification results when the data set is small or has missing values
The thesis presents a method for estimating uncertainty of classification results when there are missing values in the data. In addition, the calibration of an uncertainty measure is studied on small data sets and two algorithms to improve the calibration are presented.
Last updated: 1.3.2023