LogicForest-package:
Logic Forest
Description
Two classification ensemble methods based on logic regression models. Logforest uses a bagging approach to contruct an ensemble of logic regression models. LBoost uses a combination of boosting and cross-validation to construct and ensemble of logic regression models. Both methods are used for classification of binary responses based on binary predictors and for identification of important variables and variable interactions predictive of a binary outcome.Details
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Package: |
| LogicForest |
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Type: |
| Package |
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Version: |
| 2.0.0 |
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Date: |
| 2011-09-20 |
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License: |
| GPL-2 |
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LazyLoad: |
| yes |
References
Wolf, B.J., Slate, E.H., Hill, E.G. (2010) Logic Forest: An ensemble classifier for discovering logical combinations of binary markers. Bioinformatics.
Wolf, B.J., Hill, E.G., Slate, E.H., Neumann, C.A., Kistner-Griffin, E. (2012). LBoost: A boosting algorithm with applications for epistasis discovery. PLoS One.