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» Mining Several Data Bases with an Ensemble of Classifiers
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BMCBI
2005
251views more  BMCBI 2005»
13 years 7 months ago
Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation
Background: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very effici...
Tapio Pahikkala, Filip Ginter, Jorma Boberg, Jouni...
CIKM
2006
Springer
13 years 11 months ago
Classification spanning correlated data streams
In many applications, classifiers need to be built based on multiple related data streams. For example, stock streams and news streams are related, where the classification patter...
Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Rong She, Jian ...
ECCV
2006
Springer
13 years 11 months ago
Comparing Ensembles of Learners: Detecting Prostate Cancer from High Resolution MRI
While learning ensembles have been widely used for various pattern recognition tasks, surprisingly, they have found limited application in problems related to medical image analysi...
Anant Madabhushi, Jianbo Shi, Michael D. Feldman, ...
TKDE
2011
183views more  TKDE 2011»
13 years 2 months ago
Mining Discriminative Patterns for Classifying Trajectories on Road Networks
—Classification has been used for modeling many kinds of data sets, including sets of items, text documents, graphs, and networks. However, there is a lack of study on a new kind...
Jae-Gil Lee, Jiawei Han, Xiaolei Li, Hong Cheng
ALMOB
2006
102views more  ALMOB 2006»
13 years 7 months ago
Mining, compressing and classifying with extensible motifs
Background: Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in t...
Alberto Apostolico, Matteo Comin, Laxmi Parida