Extracting Hierarchies from Data Clusters for Better Classification

Algorithms

German Sapozhnikov¹ 

[1] Saint Petersburg State Polytechnical University, Polytechnicheskaya 29, Saint Petersburg 194064, Russia

关键词: multi-label classification;    hierarchical classification;    clustering;   

DOI  :  10.3390/a5040506

来源: mdpi

【 摘 要 】

In this paper we present the PHOCS-2 algorithm, which extracts a “Predicted Hierarchy Of ClassifierS”. The extracted hierarchy helps us to enhance performance of flat classification. Nodes in the hierarchy contain classifiers. Each intermediate node corresponds to a set of classes and each leaf node corresponds to a single class. In the PHOCS-2 we make estimation for each node and achieve more precise computation of false positives, true positives and false negatives. Stopping criteria are based on the results of the flat classification. The proposed algorithm is validated against nine datasets.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.