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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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Proceedings of the 9th Annual ACM India Conference, 2016
Decision Tree is a tree-structured plan of a set of attributes to test in order to predict the output. MapReduce and Spark is a programming model used for processing data on a distributed file system. In this paper, MapReduce and Spark implementation of Decision Tree is named as Distributed Decision Tree (DDT) and Spark Tree (ST) respectively. Decision
Ankit Desai, Sanjay Chaudhary
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Decision Tree is a tree-structured plan of a set of attributes to test in order to predict the output. MapReduce and Spark is a programming model used for processing data on a distributed file system. In this paper, MapReduce and Spark implementation of Decision Tree is named as Distributed Decision Tree (DDT) and Spark Tree (ST) respectively. Decision
Ankit Desai, Sanjay Chaudhary
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On the Decision Trees with Symmetries
2018We introduce a propositional proof system based on decision trees utilizing symmetries of formulas. We refer to this proof system as decision trees with symmetries (\(\mathrm {SDT}\)). \(\mathrm {SDT}\) can be polynomially simulated by the proof system \(\mathrm {SR}\text {-}\mathrm {I}\) introduced by Krishnamurthy [7]; \(\mathrm {SR}\text {-}\mathrm {
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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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2002
Searching for binary partition of attribute domains is an important task in Data Mining, particularly in decision tree methods. The most important advantage of decision tree methods are based on compactness and clearness of presented knowledge and high accuracy of classification.
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Searching for binary partition of attribute domains is an important task in Data Mining, particularly in decision tree methods. The most important advantage of decision tree methods are based on compactness and clearness of presented knowledge and high accuracy of classification.
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Constraint Enforcement on Decision Trees: A Survey
ACM Computing Surveys, 2022Geraldin Nanfack +2 more
exaly
Shallow decision trees for explainable k-means clustering
Pattern Recognition, 2023Eduardo Sany Laber, Lucas Murtinho
exaly
Proceedings of the 8th International Workshop on Software Specification and Design, 2002
Alexander Ran, Juha Kuusela
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Alexander Ran, Juha Kuusela
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