14 search results - page 1 / 3 » Paired Learners for Concept Drift |
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
COLT
2010
Springer
13 years 2 months ago
2010
Springer
In standard online learning, the goal of the learner is to maintain an average loss that is "not too big" compared to the loss of the best-performing function in a fixed...
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
ICDM
2003
IEEE
13 years 9 months ago
2003
IEEE
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
EPIA
2003
Springer
13 years 9 months ago
2003
Springer
Most of supervised learning algorithms assume the stability of the target concept over time. Nevertheless in many real-user modeling systems, where the data is collected over an ex...