Abstract
Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.
Recommended Citation
D. C. Wunsch et al., "Methods and Systems for Biclustering Algorithm," U.S. Patents, May 2015.
Department(s)
Electrical and Computer Engineering
Research Center/Lab(s)
Center for High Performance Computing Research
Patent Application Number
US13/385,042
Patent Number
US9043326B2
Document Type
Patent
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2015 The Curators of the University of Missouri, All rights reserved.
Publication Date
26 May 2015
Included in
Electrical and Computer Engineering Commons, Numerical Analysis and Scientific Computing Commons
