Hierarchical Ensemble Support Cluster Machine
MCS '09 Proceedings of the 8th International Workshop on Multiple Classifier Systems
Using a boosted tree classifier for text segmentation in hand-annotated documents
Pattern Recognition Letters
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We propose a novel hierarchical classification method for documents categorization in this paper. The approach consists of multiple levels of classification for different hierarchies. Regularized Least Square (RLS)binary classifiers are applied in the middle levels of the hierarchy to classify documents into smaller set of categories and K-nearest-neighbor (KNN) multi-class classifiers are used at the bottom to classify documents into final classes. Experiments on large-scale real world tax documents show that the proposed hierarchical approach outperforms traditional flat classification method.