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2017
This chapter provides further detail and depth on the construction of decision trees. Properties of expected value and decision trees are presented along with examples that demonstrate the use of probability and expected value of perfect and imperfect information.
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This chapter provides further detail and depth on the construction of decision trees. Properties of expected value and decision trees are presented along with examples that demonstrate the use of probability and expected value of perfect and imperfect information.
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2008
Decision trees are part of the decision theory and are excellent tools in the decision-making process. Majority of decision tree learning methods were developed within the last 30 years by scholars like Quinlan, Mitchell, and Breiman, just to name a few (Ozgulbas & Koyuncugil, 2006).
John Wang, Dajin Wang
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Decision trees are part of the decision theory and are excellent tools in the decision-making process. Majority of decision tree learning methods were developed within the last 30 years by scholars like Quinlan, Mitchell, and Breiman, just to name a few (Ozgulbas & Koyuncugil, 2006).
John Wang, Dajin Wang
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Collegian, 2000
Financial cutbacks and budgetary constraints continue to be a part of government policy, and impact deeply on many aspects of daily life in Australia in the late 90s. Health care is not immune from these measures, and nurses and other allied health professionals are having to manage increasingly complex patient care with less funding and resources ...
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Financial cutbacks and budgetary constraints continue to be a part of government policy, and impact deeply on many aspects of daily life in Australia in the late 90s. Health care is not immune from these measures, and nurses and other allied health professionals are having to manage increasingly complex patient care with less funding and resources ...
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Fuzzy Sets and Systems, 1980
Abstract We propose here to extend the decision trees method to the case when the involved data (probabilities, cost, profits, losses) appear as words belonging to the common language whose semantic representations are fuzzy sets. First we discuss the reasons why such an extension is to be aimed at.
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Abstract We propose here to extend the decision trees method to the case when the involved data (probabilities, cost, profits, losses) appear as words belonging to the common language whose semantic representations are fuzzy sets. First we discuss the reasons why such an extension is to be aimed at.
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Management Decision, 1995
Explores, using appropriate examples, the ways in which decision trees can be used by the manager to assist in the longitudinal decision‐making process. Since the mathematical concepts associated with decision trees are complex, managers can be reluctant to attempt to use decision tree models. A recognition that such models can be simply developed in a
Coles, Susan, Rowley, Jennifer
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Explores, using appropriate examples, the ways in which decision trees can be used by the manager to assist in the longitudinal decision‐making process. Since the mathematical concepts associated with decision trees are complex, managers can be reluctant to attempt to use decision tree models. A recognition that such models can be simply developed in a
Coles, Susan, Rowley, Jennifer
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2010
Consider a wireless sensor network in which each node possesses a bit of information. Suppose all sensors with the bit 1 broadcast this fact to a central processor. If zero or one sensors broadcast, the central processor can detect this fact. If two or more sensors broadcast, the central processor can only detect that there is a "collision." Although ...
Steve Uurtamo +5 more
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Consider a wireless sensor network in which each node possesses a bit of information. Suppose all sensors with the bit 1 broadcast this fact to a central processor. If zero or one sensors broadcast, the central processor can detect this fact. If two or more sensors broadcast, the central processor can only detect that there is a "collision." Although ...
Steve Uurtamo +5 more
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Decision Trees and Applications
2020In many cases, the meaning of information is wrongly related to either the sense of data or the notion of knowledge. There is a crucial sequence of steps before information becomes knowledge and the value of data depends in the existence of information so as to produce knowledge.
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SIZES OF ORDERED DECISION TREES
International Journal of Foundations of Computer Science, 2002Decision tables provide a natural framework for knowledge acquisition and representation in the area of knowledge based information systems. Decision trees provide a standard method for inductive inference in the area of machine learning. In this paper we show how decision tables can be considered as ordered decision trees: decision trees satisfying ...
Hans L. Bodlaender, Hans Zantema
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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).
openaire +1 more source