Supervised learning using Boltzmann Bayes model inference, which extends naive Bayes model to include interactions. Enables classification of data into multiple response groups based on a large number of discrete predictors that can take factor values of heterogeneous levels. Either pseudo-likelihood or mean field inference can be used with L2 regularization, cross-validation, and prediction on new data. Woo et al. (2016) <doi:10.1186/s12864-016-2871-3>.
Package details |
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Maintainer | Jun Woo <jwoo@umn.edu> |
License | GPL (>= 2) |
Version | 0.2.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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