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IJCAI
2001
13 years 10 months ago
Using Text Classifiers for Numerical Classification
Consider a supervised learning problem in which examples contain both numerical- and text-valued features. To use traditional featurevector-based learning methods, one could treat...
Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, ...
AIEDU
2007
93views more  AIEDU 2007»
13 years 9 months ago
UMPTEEN: Named and Anonymous Learner Model Access for Instructors and Peers
Recently, opening the learner model to the learner it represents has become more common in adaptive learning environments. There have also been systems that allow instructors acces...
Susan Bull, Andrew Mabbott, Abdallatif S. Abu-Issa
JCP
2008
121views more  JCP 2008»
13 years 8 months ago
Relation Organization of SOM Initial Map by Improved Node Exchange
The Self Organizing Map (SOM) involves neural networks, that learns the features of input data thorough unsupervised, competitive neighborhood learning. In the SOM learning algorit...
Tsutomu Miyoshi
CGF
2005
252views more  CGF 2005»
13 years 8 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
ICDM
2010
IEEE
178views Data Mining» more  ICDM 2010»
13 years 6 months ago
Exploiting Unlabeled Data to Enhance Ensemble Diversity
Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate a...
Min-Ling Zhang, Zhi-Hua Zhou