The Dynamics of AdaBoost Weights Tells You What's Hard to Classify

Details The Dynamics of AdaBoost Weights Tells You What's Hard to Classify The Dynamics of AdaBoost Weights Tells You What's Hard to Classify

2002-01-17

arxiv.org/abs/cs/0201014v1

Computer Science

Learning

7 pages, LaTeX, 4 figures

Scientific paper

The dynamical evolution of weights in the Adaboost algorithm contains useful information about the role that the associated data points play in the built of the Adaboost model. In particular, the dynamics induces a bipartition of the data set into two (easy/hard) classes. Easy points are ininfluential in the making of the model, while the varying relevance of hard points can be gauged in terms of an entropy value associated to their evolution. Smooth approximations of entropy highlight regions where classification is most uncertain. Promising results are obtained when methods proposed are applied in the Optimal Sampling framework.

Affiliated with

Also associated with

No associations

Rating

The Dynamics of AdaBoost Weights Tells You What's Hard to Classify does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with The Dynamics of AdaBoost Weights Tells You What's Hard to Classify, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Dynamics of AdaBoost Weights Tells You What's Hard to Classify will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-484434