Results 291 to 300 of about 305,651 (314)

Hybrid decision tree

Knowledge-Based Systems, 2002
In this paper, a hybrid learning approach named hybrid decision tree (HDT) is proposed. HDT simulates human reasoning by using symbolic learning to do qualitative analysis and using neural learning to do subsequent quantitative analysis. It generates the trunk of a binary HDT according to the binary information gain ratio criterion in an instance space
Zhi-Hua Zhou, Zhaoqian Chen
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Fisher’s decision tree

Expert Systems with Applications, 2013
Univariate decision trees are classifiers currently used in many data mining applications. This classifier discovers partitions in the input space via hyperplanes that are orthogonal to the axes of attributes, producing a model that can be understood by human experts.
Asdrúbal López-Chau, Jair Cervantes, Lourdes López-García, Farid García-Lamont   +3 more
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Decision Trees for Decision Tables

1994
We 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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On decision trees for orthants

Information Processing Letters, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Optimization of the decision tree

[Proceedings] Third International Conference on Tools for Artificial Intelligence - TAI 91, 2002
An approach is presented to the optimization of decision trees. A decision tree is considered optimal if it correctly classifies the known data set and has the minimal number of nodes. It is shown that it is important to decide the right order of attributes to test, for this can reduce the number of checking nodes in a decision tree. >
Won Chan Jung, J. Bush Jones, Jianhua Chen 0003   +2 more
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Decision trees with AND, OR queries

Proceedings of Structure in Complexity Theory. Tenth Annual IEEE Conference, 2002
We investigate decision trees in which one is allowed to query threshold functions of subsets of variables. We are mainly interested in the case where only queries of AND and OR are allowed. This model is a generalization of the classical decision tree model.
Yosi Ben-Asher, Ilan Newman
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Decision Trees and Applications

2020
In 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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Distributed Decision Tree

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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Interpretable hierarchical clustering by constructing an unsupervised decision tree

IEEE Transactions on Knowledge and Data Engineering, 2005
R Krishnapuram
exaly  

Decision tree regression for soft classification of remote sensing data

Remote Sensing of Environment, 2005
P Watanachaturaporn, Pramod K Varshney, Manoj K Arora   +2 more
exaly