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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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2008
The first (crisp) decision tree techniques were introduced in the 1960s (Hunt, Marin, & Stone, 1966), their appeal to decision makers is due in no part to their comprehensibility in classifying objects based on their attribute values (Janikow, 1998).
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The first (crisp) decision tree techniques were introduced in the 1960s (Hunt, Marin, & Stone, 1966), their appeal to decision makers is due in no part to their comprehensibility in classifying objects based on their attribute values (Janikow, 1998).
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Decision analysis by decision tree
Omega, 1973Abstract The process of decision analysis by decision tree for any decision maker may essentially be summarized as follows: 1. (a) Form the decision tree for the problem; 2. (b) Quantify your judgement by assigning subjective probabilities to the possible outcomes in the decision tree; 3.
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Multicriteria decision analysis in a decision tree
European Journal of Operational Research, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Avoiding Overfitting of Decision Trees
Principles of Data Mining, 2020M. Bramer
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Decision Trees for Decision Tables
1994We investigate decision trees for decision tables. We present some upper and lower bounds on the minimal decision tree depth. These bounds are expressed by some parameters of decision rule systems constructed for decision tables.
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Data Mining with Decision Trees: Theory and Applications
Online information review (Print), 2015Andreas Holzinger
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