UPMC-LIP6 at TrecVid'08: Balanced and Unbalanced Forests of Fuzzy Decision Trees for High-Level Feature Detection

Christophe Marsala (1) , Marcin Detyniecki (1)

1 MALIRE - Machine Learning and Information Retrieval

In this paper, we present the methodology we applied in our submission to the NIST TRECVID’2008 evaluation. We participated in the High-level Feature Extraction task. Our approach is based on the use of a Forest of Fuzzy Decision Trees constructed by means of either a balanced sampling of the development data, or an unbalanced sampling of the development data.

Domaines: Informatique [cs]

Christophe Marsala, Marcin Detyniecki. UPMC-LIP6 at TrecVid'08: Balanced and Unbalanced Forests of Fuzzy Decision Trees for High-Level Feature Detection. TRECVID 2008 workshop participants notebook papers, Nov 2008, Gaithersburg, MD, United States. ⟨hal-01305038⟩