Decision Forest

Tong, W., Hong, H., Fang, H., Xie, Q., and Perkins, R. (2003) Decision forest combining the predictions of multiple independent decision tree models../. Chem. Inf. Comput. Sci. 43, 525-531. 

Figure 6.4 Illustration of the decision forest (DF). The individual trees are developed sequentially, and each tree uses a distinct set of descriptors. Classification (i.e., prediction) of an unknown chemical is based on the mean results of all trees.

The Decision Forest (DF) is a DT-based consensus modeling method that was conceived as a method for combining heterogeneous yet comparable trees that fully captures the association between molecular structure and biological activity (Figure 6.4) [59], The heterogeneity requirement assures that each tree uniquely contributes to the combined prediction whereas the quality comparability requirement assures that each tree equally contributes to the combined prediction. 

Active/Inactive Assignment. . Structural alerts Pharmacophores Decision Tree (or Decision Forest) Shape Signatures... 

Tong W, Hong H, Fang H, Xie Q, Perkins R. Decision forest Combining the predictions of multiple independent decision tree model. J Chem Inf Comput Sci 2003 43 525-31. 

At NCTR an alternative priority-setting model, called Decision Forest [67,68], was developed. In this model the results of multiple heterogeneous... 

Hong H, Tong W, Xie Q, Fang H, Perkins R. An in silico ensemble method for lead discovery decision forest. SAR QSAR Environ Res 2005 16(4) 339-347. 

Ho, T. K. (1998). The random subspace method for constructing decision forests. IEEE Trans. Pattern Anal. Machine IntelL, 20 832-844. 

At each internal tree node, a decision forest randomly can select F feature attributes, and evaluate just those attributes to choose the partitioning attribute. They tend to produce trees larger than trees where all attributes are considered for selection at each node, but different classes will be eventually assigned to different leaf nodes. At each internal tree node, RFs evaluate the quality of all possible partitioning attributes, but randomly select one of the Fbest attributes to label that node based on information gain, etc. RFs are an effective tool in prediction compared with boosting and adaptive bagging. 

Decision authorizing the Member States to permit temporanly the marketing of forest reproductive... 

EPA. 1986d. Superfund record of decision (EPA Region 5) Forest waste disposal site, Genesee County, Michigan. PB87-189890. 

It is important to emphasize that forestry is a long-term industry. Decisions taken now concerning the way in which we manage our forests will have an effect way into the future, perhaps as much as a century later. 

The women announced that we would eliminate breakfast and lunch to make better time. It was their decision since they were doing the cooking it was too much of a chore to make a fire in the damp Amazonian forest. 

Better understanding of allelochemicals in plant population dynamics in ecosystems will provide a basis for improved management decisions for managers of rangelands and forests. This will be especially significant for ecosystems undergoing drastic changes such as a forest that has burned or has been harvested. 

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