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» Multiple labels associative classification
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ICML
2004
IEEE
15 years 10 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ML
2000
ACM
124views Machine Learning» more  ML 2000»
14 years 9 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
14 years 7 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
ICMCS
2007
IEEE
124views Multimedia» more  ICMCS 2007»
15 years 3 months ago
Video Semantic Concept Discovery using Multimodal-Based Association Classification
Digital audio and video have recently taken a center stage in the communication world, which highlights the importance of digital media information management and indexing. It is ...
Lin Lin, Guy Ravitz, Mei-Ling Shyu, Shu-Ching Chen
SAC
2010
ACM
14 years 4 months ago
A study on interestingness measures for associative classifiers
Associative classification is a rule-based approach to classify data relying on association rule mining by discovering associations between a set of features and a class label. Su...
Mojdeh Jalali Heravi, Osmar R. Zaïane