Saarland University, Machine Learning Group, Fak. MI - Mathematik und Informatik, Campus E1 1, 66123 Saarbr├╝cken, Germany     

Machine Learning Group
Department of Mathematics and Computer Science - Saarland University


a Matlab GUI to explore semi-supervised learning and the influence of different similarity graphs

by Matthias Hein and Ulrike von Luxburg


DemoSSL: The purpose of this demo is to show how graph-based semi-supervised learning depends on the graph structure, the amount of labeled data and the regularization parameter. As algorithm we use the one proposed by Zhou et al: "Learning with local and global consistency" .


DemoSSL has been used for teaching purposes at the Machine Learning Summer School 2007 in Tuebingen, Germany. The tutorial presents the theoretical basis of the algorithm of Zhou as well as of related ones. The influences of the different parameters on the classification results of the semisupervised learning algorithm are discussed, too.

Download tutorial on semi-supervised learning   

SCREENSHOT OF DemoSimilarityGraphs