decision tree

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decision tree

n
a treelike diagram illustrating the choices available to a decision maker, each possible decision and its estimated outcome being shown as a separate branch of the tree
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A regression tree using only the top variables identified within the randomForest measures of importance (depth of water, pH, distance from springhead, and density of pond snails) explained 36.
Regression tree classifications successfully separated habitats of high and low abalone densities, but these differed from habitats classified using mean shell length as the response variable.
A classification tree analysis was conducted using CART[R] (Classification and Regression Tree, 2005) to classify who was more likely to use online employer-provided retirement investment advice.
Despite certain limitations, results obtained by the regression tree suggest that higher alcohol consumption per se and long-term intermittent, moderate exposure to [Hg.
The study uses a classification and regression tree that attempts to profile students by using demographic and academic factors as predictors of disability status including age, ethnicity, gender, GPA, etc.
Unlike previous years, however, segmentation of this spring's database was further optimized using Salford Systems' CART regression tree software.
Finally, by using CSF and serum neopterin concentrations and liquor lymphocytic cell count as candidate variables, we constructed a classification tree for the discrimination between the four diagnostic categories (controls, neuroborreliosis, other CNS infections, and peripheral infections) by using the classification and regression tree (CART) technique [15].
The aim of this study was to evaluate predictive performances of CHAID, Exhaustive CHAID, and CART regression tree methods for different combinations of parent node: child node in the data set regarding animal science.
The analyses involved the development of Poisson boosted regression tree (BRT) models to predict the daily incidence rate of H7N9 virus in the human population as a function of 6 predictor variables.
Beekeeping, Honey yield, Regression tree analysis, Data mining, Production economics.
Neither RE nor fixed effects are known, and we alternate between estimating the regression tree, assuming that our estimates of the RE are correct and estimating the RE, assuming that the regression tree is correct.
The implicit method employs a regression tree approach (Quinlan 1996) with an embedded nearest neighbor scheme to forecast both deterministic irradiance and its variability (McCandless et al.