Results 81 to 90 of about 1,054,775 (163)
On Decision Trees, Influences, and Learning Monotone Decision Trees
In this note we prove that a monotone boolean function computable by a decision tree of size s has average sensitivity at most √ log2 s. As a consequence we show that monotone functions are learnable to constant accuracy under the uniform distribution in time polynomial in their decision tree size.
O'Donnell, Ryan, Servedio, Rocco Anthony
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This paper addresses the issue of the induction of orthogonal, oblique and multivariate decision trees. Algorithms proposed by other researchers use heuristic, usually based on the information gain concept, to induce decision trees greedily. These algorithms are often tailored for a given tree type ( e.g orthogonal), not being able to induce other ...
Llorà Fàbrega, Xavier+1 more
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Rockburst prediction in kimberlite using decision tree with incomplete data
A rockburst is a common engineering geological hazard. In order to predict rockburst potential in kimberlite at an underground diamond mine, a decision tree method was employed.
Yuanyuan Pu, Derek B. Apel, Bob Lingga
doaj
The goal of this paper is to reduce the classification (inference) complexity of tree ensembles by choosing a single representative model out of ensemble of multiple decision-tree models. We compute the similarity between different models in the ensemble
Abraham Itzhak Weinberg, Mark Last
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An Automated Approach to the Design of Decision Tree Classifiers [PDF]
P. Argentiero+2 more
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An Application of Computerized Decision Tree Models in Management-Union Bargaining [PDF]
Frederick W. Winter
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Probabilistic, nondeterministic, and alternating decision trees (Preliminary Version) [PDF]
Udi Manber, Martin Tompa
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MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees
Decision trees remain one of the most popular machine learning models today, largely due to their out-of-the-box performance and interpretability. In this work, we present a Bayesian approach to decision tree induction via maximum a posteriori inference of a posterior distribution over trees.
Sullivan, Colin+2 more
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