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Dforest: Decision Forest
Provides R-implementation of Decision forest algorithm, which combines the predictions of multiple independent decision tree models for a consensus decision. In particular, Decision Forest is a novel pattern-recognition method which can be used to analyze: (1) DNA microarray data; (2) Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (SELDI-TOF-MS) data; and (3) Structure-Activity Relation (SAR) data. In this package, three fundamental functions are provided, as (1)DF_train, (2)DF_pred, and (3)DF_CV. run Dforest() to see more instructions. Weida Tong (2003) <doi:10.1021/ci020058s>.
Getting started
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Package details |
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| Author | Leihong Wu <leihong.wu@fda.hhs.gov>, Weida Tong (Weida.tong@fda.hhs.gov) |
| Maintainer | Leihong Wu <leihong.wu@fda.hhs.gov> |
| License | GPL-2 |
| Version | 0.4.2 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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