2712 search results - page 24 / 543 » On learning algorithm selection for classification |
CIKM
2008
Springer
13 years 9 months ago
2008
Springer
Proactive learning is a generalization of active learning designed to relax unrealistic assumptions and thereby reach practical applications. Active learning seeks to select the m...
GECCO
2007
Springer
14 years 1 months ago
2007
Springer
Selecting the most relevant factors from genetic profiles that can optimally characterize cellular states is of crucial importance in identifying complex disease genes and biomark...
EWCBR
2006
Springer
13 years 11 months ago
2006
Springer
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
Classifying high-dimensional numerical data is a very challenging problem. In high dimensional feature spaces, the performance of supervised learning methods suffer from the curse...