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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 9 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
AIIA
2009
Springer
15 years 8 months ago
Local Kernel for Brains Classification in Schizophrenia
Abstract. In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining loc...
Umberto Castellani, E. Rossato, Vittorio Murino, M...
CEC
2007
IEEE
15 years 8 months ago
Evolving hypernetworks for pattern classification
Abstract-- Hypernetworks consist of a large number of hyperedges that represent higher-order features sampled from training patterns. Evolutionary algorithms have been used as a me...
Joo-Kyung Kim, Byoung-Tak Zhang
CIKM
2009
Springer
15 years 8 months ago
Ensembles in adversarial classification for spam
The standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. As the spammers change their tactics, the performanc...
Deepak Chinavle, Pranam Kolari, Tim Oates, Tim Fin...
CIVR
2006
Springer
139views Image Analysis» more  CIVR 2006»
15 years 7 months ago
NPIC: Hierarchical Synthetic Image Classification Using Image Search and Generic Features
We introduce NPIC, an image classification system that focuses on synthetic (e.g., non-photographic) images. We use class-specific keywords in an image search engine to create a no...
Fei Wang, Min-Yen Kan