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SSPR
1998
Springer
13 years 8 months ago
Modified Minimum Classification Error Learning and Its Application to Neural Networks
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Hiroshi Shimodaira, Jun Rokui, Mitsuru Nakai
PR
2010
147views more  PR 2010»
13 years 2 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
ICANN
2003
Springer
13 years 9 months ago
Confidence Estimation Using the Incremental Learning Algorithm, Learn++
Pattern recognition problems span a broad range of applications, where each application has its own tolerance on classification error. The varying levels of risk associated with ma...
Jeffrey Byorick, Robi Polikar
IJISTA
2007
124views more  IJISTA 2007»
13 years 4 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
NN
2007
Springer
105views Neural Networks» more  NN 2007»
13 years 4 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling