Bibliography on estimation of misclassification

Authors:
G. Toussaint
Affiliations:
-
Venue:
IEEE Transactions on Information Theory
Year:
2006

Citing 0
Cited 8

A local mean-based nonparametric classifier

Pattern Recognition Letters
Editorial: The fundamental role of pattern recognition for gene-expression/microarray data in bioinformatics

Pattern Recognition
Update methods for reduction of computing time in simulation studies

Computational Statistics & Data Analysis
The asymptotic distribution of an estimator of the Bayes error rate

Pattern Recognition Letters
Decision rules for a hierarchical classifier

Pattern Recognition Letters
Application of bootstrap and other resampling techniques: Evaluation of classifier performance

Pattern Recognition Letters
Sequential testing in classifier evaluation yields biased estimates of effectiveness

Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
Towards minimizing the annotation cost of certified text classification

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management

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Abstract

Articles, books, and technical reports on the theoretical and experimental estimation of probability of misclassification are listed for the case of correctly labeled or preclassified training data. By way of introduction, the problem of estimating the probability of misclassification is discussed in order to characterize the contributions of the literature.