Print Email Facebook Twitter Rule Induction on Multiple Instance Learning Concepts Title Rule Induction on Multiple Instance Learning Concepts Author van der Wal, Robin (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Tax, D.M.J. (mentor) Reinders, M.J.T. (graduation committee) Wang, H. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science Date 2022-10-25 Abstract Multiple Instance Learning (MIL) is a type of semi-supervised machine learning used recently in medical and multi-media fields. In MIL, instead of a single feature vector, a set of feature vectors has to be classified. Standard MIL algorithms assume that only some of these vectors are useful for building a classifier. This paper extends the standard MIL assumption by combining propositional logic and classical MIL classifiers. Adding propositional logic allows for increased interpretability as it establishes an if-then relationship between the input data and the output classes. This combination of logic and classical MIL classifiers will be called Concept Rule Induction (CRI). CRI is tested on several artificial and real-life bird song data. CRI is shown to work for these data sets, and the rules produced by propositional logic can be interpreted Subject Multiple Instance LearningRule InductionAudio ClassificationFrameworkNon-LinearClustering To reference this document use: http://resolver.tudelft.nl/uuid:3f61e0d9-601c-4530-93a3-49e126735b7d Part of collection Student theses Document type master thesis Rights © 2022 Robin van der Wal Files PDF thesisRobinvanderWal_v1.pdf 3.6 MB Close viewer /islandora/object/uuid:3f61e0d9-601c-4530-93a3-49e126735b7d/datastream/OBJ/view