README.md
In ryanholbrook/bayeserror: Estimating Bayes Error in Classification Tasks
bayeserror
This package (will eventually) implement several estimators of the
Bayes error rate of a
data set for a classification task. The Bayes error rate is a measure of
how well the features of the data can discriminate among the classes. It
gives the best possible error rate attainable from the data. If the
distributions of the classes overlap, then the Bayes error rate must be
greater than zero.
There are three parametric estimates: 1. Mahalanobis distance 2.
Bhattacharyya distance 3. Chernoff bound
And three non-parametric estimates: 4. Nearest Neighbor 5. Classifier
Ensembles 6. Plurality Error
ryanholbrook/bayeserror documentation built on Jan. 12, 2020, 6:25 p.m.
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bayeserror
This package (will eventually) implement several estimators of the Bayes error rate of a data set for a classification task. The Bayes error rate is a measure of how well the features of the data can discriminate among the classes. It gives the best possible error rate attainable from the data. If the distributions of the classes overlap, then the Bayes error rate must be greater than zero.
There are three parametric estimates: 1. Mahalanobis distance 2. Bhattacharyya distance 3. Chernoff bound
And three non-parametric estimates: 4. Nearest Neighbor 5. Classifier Ensembles 6. Plurality Error
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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