Computing, School of
School of Computing: Technical Reports
Accessibility Remediation
If you are unable to use this item in its current form due to accessibility barriers, you may request remediation through our remediation request form.
Date of this Version
2011
Document Type
Article
Citation
Department of Computer Science & Engineering, University of Nebraska-Lincoln, Technical Report, TR-UNL-CSE-2011-0013
Abstract
Machine learning algorithms detects patterns, regularities, and rules from the training data and adjust program actions accordingly. For example, when a learner (a computer program) sees a set of patient cases (patient records) with corresponding diagnoses, it can predict the presence of a disease for future patients. A somewhat unrealistic assumption in typical machine learning applications is that data is freely available. In my dissertation, I will present our research efforts to mitigate this assumption in the areas of active machine learning and budgeted machine learning.
Comments
Copyright 2011 University of Nebraska-Lincoln.