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A decision-tree model to evaluate the impacts of workforce investments aimed at strengthening emergency obstetric and neonatal care (EmONC) facilities in Burundi. [PDF]
Cost Eff Resour AllocHabonimana D +10 more
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Economic Theory, 2005 The traditional model of sequential decision making, for instance, in extensive form games, is a tree. Most texts define a tree as a connected directed graph without loops and a distinguished node, called the root. But an abstract graph is not a domain for decision theory.
Alós-Ferrer, C., Ritzberger, K.
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IEEE Transactions on Knowledge and Data Engineering, 2021
Current decision trees such as C4.5 and CART are widely used in different fields due to their simplicity, accuracy and intuitive interpretation. Similar to other popular classifiers, these tree-based classification algorithms are developed for fixed-length vector data and suffer from intrinsic limitations in handling complex data such as sequences.
Zengyou He +4 more
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Current decision trees such as C4.5 and CART are widely used in different fields due to their simplicity, accuracy and intuitive interpretation. Similar to other popular classifiers, these tree-based classification algorithms are developed for fixed-length vector data and suffer from intrinsic limitations in handling complex data such as sequences.
Zengyou He +4 more
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Intelligent Data Analysis, 2000
The article presents the extension of a common decision tree concept to a multidimensional -- vector -- decision tree constructed with the help of evolutionary techniques. In contrary to the common decision tree the vector decision tree can make more than just one suggestion per input sample.
Matej Sprogar +4 more
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The article presents the extension of a common decision tree concept to a multidimensional -- vector -- decision tree constructed with the help of evolutionary techniques. In contrary to the common decision tree the vector decision tree can make more than just one suggestion per input sample.
Matej Sprogar +4 more
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Knowledge and Information Systems, 2008
Ranking problems have recently become an important research topic in the joint field of machine learning and information retrieval. This paper presented a new splitting rule that introduces a metric, i.e., an impurity measure, to construct decision trees for ranking tasks.
Fen Xia +3 more
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Ranking problems have recently become an important research topic in the joint field of machine learning and information retrieval. This paper presented a new splitting rule that introduces a metric, i.e., an impurity measure, to construct decision trees for ranking tasks.
Fen Xia +3 more
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2011 International Conference on Computer Vision, 2011
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fields (CRF) which have been widely used in computer vision. In a typical CRF model the unary potentials are derived from sophisticated random forest or boosting based classifiers,
Sebastian Nowozin +5 more
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This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fields (CRF) which have been widely used in computer vision. In a typical CRF model the unary potentials are derived from sophisticated random forest or boosting based classifiers,
Sebastian Nowozin +5 more
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Decision trees and decision-making
IEEE Transactions on Systems, Man, and Cybernetics, 1990Various practical systems capable of extracting descriptive decision-making knowledge from data have been developed and evaluated. Techniques that represent knowledge about classified tasks in the form of decision trees are examined. A sample of techniques is sketched, ranging from basic methods of constructing decision trees to ways of using them ...
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Journal of the ACM, 1990
The reduction algorithm is a technique for improving a decision tree in the abseence of aproecise cost criterion. The result of applying the algorithm is an irreducible tree that is no less efficient than the original, and may be more efficient. Irreducible trees arise in discrete decision theory as an algebraic form for decision trees.
J. Robin B. Cockett, J. A. Hierrera
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The reduction algorithm is a technique for improving a decision tree in the abseence of aproecise cost criterion. The result of applying the algorithm is an irreducible tree that is no less efficient than the original, and may be more efficient. Irreducible trees arise in discrete decision theory as an algebraic form for decision trees.
J. Robin B. Cockett, J. A. Hierrera
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On Optimization of Decision Trees
2005In the paper algorithms are considered which allow to consecutively optimize decision trees for decision tables with many-valued decisions relatively different complexity measures such as number of nodes, weighted depth, average weighted depth, etc. For decision tables over an arbitrary infinite restricted information system [5] these algorithms have ...
Igor Chikalov +2 more
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