Prediction algorithms and confidence measures based on algorithmic randomness theory

Authors:
Alex Gammerman;Volodya Vovk
Affiliations:
Computer Learning Research Centre and Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK;Computer Learning Research Centre and Department of Computer Science, Royal Holloway, University of London, Egham, Surrey TW20 0EX, UK
Venue:
Theoretical Computer Science - Natural computing
Year:
2002

Citing 6
Cited 16

Handwritten digit recognition with a back-propagation network

Advances in neural information processing systems 2
An introduction to Kolmogorov complexity and its applications (2nd ed.)

An introduction to Kolmogorov complexity and its applications (2nd ed.)
Ridge Regression Confidence Machine

ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Machine-Learning Applications of Algorithmic Randomness

ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Transduction with Confidence and Credibility

IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Learning by transduction

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence

Detecting outliers using transduction and statistical testing

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Network anomaly detection based on TCM-KNN algorithm

ASIACCS '07 Proceedings of the 2nd ACM symposium on Information, computer and communications security
Credible Case-Based Inference Using Similarity Profiles

IEEE Transactions on Knowledge and Data Engineering
TCM-KNN scheme for network anomaly detection using feature-based optimizations

Proceedings of the 2008 ACM symposium on Applied computing
A Novel Data Mining Method for Network Anomaly Detection Based on Transductive Scheme

ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Off-Line Learning with Transductive Confidence Machines: An Empirical Evaluation

MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
A Comparison of Two Approaches to Classify with Guaranteed Performance

PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
A lightweight web server anomaly detection method based on transductive scheme and genetic algorithms

Computer Communications
Cancer informatics by prototype networks in mass spectrometry

Artificial Intelligence in Medicine
Relabeling algorithm for retrieval of noisy instances and improving prediction quality

Computers in Biology and Medicine
TCM-KNN algorithm for supervised network intrusion detection

PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
Optimizing network anomaly detection scheme using instance selection mechanism

GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Topology preserving SOM with transductive confidence machine

DS'10 Proceedings of the 13th international conference on Discovery science
Learning model trees from evolving data streams

Data Mining and Knowledge Discovery
Strangeness minimisation feature selection with confidence machines

IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Quantifying the reliability of fault classifiers

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reviews some theoretical and experimental developments in building computable approximations of Kolmogorov's algorithmic notion of randomness. Based on these approximations a new set of machine learning algorithms have been developed that can be used not just to make predictions but also to estimate the confidence under the usual iid assumption.