Sentence examples for decision tree models from inspiring English sources

DF is a consensus modeling technique (Tong et al. 2003b) that combines multiple Decision Tree models (hereafter called trees) in a manner that results in more accurate predictions.

Specifically, we present algorithms for solving decision tree models and influence diagram models of sequential decision problems.

The proposed uncertainty measure is based on multiple realizations of individual and randomized decision tree models.

Conclusion: Decision tree models can be used to predict cesarean delivery.

We evaluate the proposed Bayesian network model, comparing it to traditional decision tree models, to examine its utility.

Physicochemical, structural, and topological connectivity indices and E-state key descriptors were used for obtaining the decision tree models.

For decision tree models, we propose a mixed integer programming formulation that is valid for a subclass of RDU models (corresponding to risk seeking behaviors).

The decision tree models indicated the main factors influencing the abundance of functional groups were soil Olsen-P, soil mineral nitrogen and soil pHwater.

The successful integration of environmental variables influencing the abundance of functional groups with decision tree models provided a new approach to the sustainable management of pasture functional groups.

Referring to two case studies the paper presents how to calculate and map ecological defined regions from geodata by use of decision tree models and GIS-techniques.

Decision tree models were trained from 1135 observations of soil drainage classes and validated using leave-one-out cross validation and a hold-out validation sample with 567 observations.