A Mixed Ensemble Approach for the Semi-Supervised Problem

In this paper we introduce a mixed approach for the semi-supervised data problem. Our approach consists of an ensemble unsupervised learning part where the labeled and unlabeled points are segmented into clusters. Continuing, we take advantage of the a priori information of the labeled points to assign classes to clusters and proceed to predicting with the ensemble method new incoming ones. Thus, we can finally conclude classifying new data points according to the segmentation of the whole set and the association of its clusters to the classes. / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_42b
Date January 2002
CreatorsDimitriadou, Evgenia, Weingessel, Andreas, Hornik, Kurt
PublisherSFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypePaper, NonPeerReviewed
Formatapplication/pdf
Relationhttp://epub.wu.ac.at/56/

Page generated in 0.0024 seconds