A Mixed Ensemble Approach for the Semi-Supervised Problem

Dimitriadou, Evgenia and Weingessel, Andreas and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911 (2002) A Mixed Ensemble Approach for the Semi-Supervised Problem. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 77. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

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.

Item Type: Paper
Keywords: Maschinelles Lernen / Klassifikator <Informatik> / Cluster
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Marketing > Service Marketing und Tourismus
Depositing User: Repository Administrator
Date Deposited: 04 Feb 2003 12:09
Last Modified: 24 Oct 2019 13:41
URI: https://epub.wu.ac.at/id/eprint/56

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