Open AccessBook
An Introduction to Computational Learning Theory
Michael Kearns,Umesh Vazirani +1 more
Reads0
Chats0
TLDR
The probably approximately correct learning model Occam's razor the Vapnik-Chervonenkis dimension weak and strong learning learning in the presence of noise inherent unpredictability reducibility in PAC learning learning finite automata is described.Abstract:
The probably approximately correct learning model Occam's razor the Vapnik-Chervonenkis dimension weak and strong learning learning in the presence of noise inherent unpredictability reducibility in PAC learning learning finite automata by experimentation appendix - some tools for probabilistic analysis.read more
Citations
More filters
Practical structured learning techniques for natural language processing
TL;DR: This thesis presents Searn (for “search-learn”), an approach to learning for structured outputs that is applicable to the wide variety of problems encountered in natural language (and, hopefully, to problems in other domains, such as vision and biology).
Journal ArticleDOI
Comparing Bayes model averaging and stacking when model approximation error cannot be ignored
TL;DR: Bayes Model Averaging is compared to a non-Bayes form of model averaging called stacking and the results suggest the stacking has better robustness properties than BMA in the most important settings.
Journal ArticleDOI
A case study of applying boosting naive Bayes to claim fraud diagnosis
TL;DR: The weight of evidence reformulation of AdaBoosted naive Bayes scoring due to Ridgeway et al. (1998) is applied to the problem of diagnosing insurance claim fraud and is revealed to be a valuable contribution to the design of intelligible, accountable, and efficient fraud detection support.
Proceedings ArticleDOI
Predicting rare classes: can boosting make any weak learner strong?
TL;DR: This analysis indicates that one cannot be blind to the base learner performance, and just rely on the boosting mechanism to take care of its weakness, and validate the arguments empirically on variety of real and synthetic rare class problems.
DissertationDOI
An integrated approach to testing complex systems
TL;DR: The integrated test approach is presented, which offers a coarse grained test environment realized in terms of a component-based test design on top of a library of elementary but intuitively understandable test case fragments, and an algorithm for generating approximate models for complex systems a posteriori is provided.