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CART was used to build a regression tree with a dependent variable as the priority score.
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Others have built a regression tree for each target gene, using a compact set of regulators at each node [ 31- 34].
Pedotransfer functions were built using a regression tree model on a subset of the data for which total Si concentration was measured.
This includes multiple hypothesis testing and a regression tree that builds a parsimonious and predictive model of the suitable configurations of the parameters.
Neuropathy incidence and severity were curated from drug labels and literature and were used to build a predictive model of DIPN using a regression tree algorithm, based on the drug targets and their intermediators.
The best model built by M5P when using as input the 12 predicted log Kt:p descriptors for different tissues is a regression tree where log Kskin:plasma is the most relevant descriptor, occurring at the tree's root node.
We also trained a regression tree with full cross-validation.
For bagged regression trees, a regression tree was grown in each of 100 bootstrap samples.
The tree can be either a classification tree or a regression tree, and a common term including both is classification and regression tree (CART).
In our implementation of RFML, a temporary validation dataset is created to build each regression tree, and is chosen as a randomly selected set of 250 samples left out of the full training dataset.
The ID3 algorithm can be used to build a decision tree for regression by changing Information Gain with Standard Deviation Reduction.
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