Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications

Development of Partially Supervised Kernel-based Proximity Clustering Frameworks and Their Applications

The focus of this study is the development and evaluation of a new partially supervised learning framework. This framework belongs to an emerging field in machine learning that augments unsupervised learning processes with some elements of supervision. It is based on proximity fuzzy clustering, wher...

Full description

Bibliographic Details
Main Author: Graves, Daniel
Other Authors: Pedrycz, Witold (Electrical and Computer Engineering)
Format: Others
Language:en_US
Published: 2011
Subjects:
Partially supervised learning
Fuzzy clustering
Proximity hints
Kernel-based clustering
Active learning
Multi-proximity clustering
Time series analysis
Time series clustering
Structural musical segmentation
Graph clustering
Online Access:http://hdl.handle.net/10048/1694

Internet

http://hdl.handle.net/10048/1694

Similar Items