| Acronym: EMUSuL |
| Main Objective: This is a fundamental research project in the area of machine learning. Accordingly, the goals are of methodological, theoretical and algorithmic nature. More specifically, the project aims at: - developing cluster combination techniques, in which partitions, clusters and even samples can assume different weights in the combination strategies. - integrating common and state-of-the-art clustering algorithms in the combination process - creating a theoretical framework for the analysis of clustering combination techniques and cluster validity - extending combination techniques used in supervised and unsupervised learning to the semi-supervised scenario. - applying the developed methodologies to challenging learning problems (both unsupervised and semi-supervised), such as document classification, web page classification, and gene-expression data analysis. |
| Reference: POSC/EEA-SRI/61924/2004 |
| Funding: FCT/POSC |
| Start Date: 01-01-2005 |
| End Date: 31-12-2007 |
| Team: Mario Alexandre Teles de Figueiredo, Ana Luisa Nobre Fred, Sandra V. B. Jardim |
| Groups: Pattern and Image Analysis – Lx |
| Partners: Instituto Superior de Engenharia do Porto |
| Local Coordinator: Mario Alexandre Teles de Figueiredo |
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Associated Publications
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