Machine learning supervised method to learn rare genomic features in imbalanced genetic data sets. This method can be also applied to classify or rank examples characterized by a high imbalance between the minority and majority class. hyperSMURF adopts a hyper-ensemble (ensemble of ensembles) approach, undersampling of the majority class and oversampling of the minority class to learn highly imbalanced data.
|Author||Giorgio Valentini [aut, cre] - AnacletoLab, Dipartimento di Informatica, Universita' degli Studi di Milano; Max Schubach [ctb] - Charite, Universitatsmedizin Berlin; Matteo Re [ctb] - AnacletoLab, Dipartimento di Informatica, Universita' degli Studi di Milano; Peter N Robinson [ctb] - The Jackson Laboratory for Genomic Medicine, Farmington CT, USA.|
|Maintainer||Giorgio Valentini <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
Install the latest version of this package by entering the following in R:
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.