Reliable and Comprehensible Machine Learning Approaches with Applications to Medical Diagnostics and Bioinformatics Bilateral

Client ID: Agencija za raziskovalno dejavnost RS
Project type: Bilateral Collaboration Project
Project duration: 2005 - 2007

Collaborators on project


Usually machine learning algorithms provide only bare predictions (classifications) for new unclassified examples (test cases). While there are ways for almost all machine learning algorithms to at least partially provide quantitative assessment of the particular classification, so far there is no general method to assess the quality (confidence, reliability) of the classification decision made for a new case. In this collaborative research project we elaborated on the very important issues of how to assess the performance of a classifier on a single case and not on the average performance for a certain set of cases and solved some of the problems so that the method became closer to generally applicable method.