Optimization of Decision Trees with Hypotheses for Knowledge Representation

Optimization of Decision Trees with Hypotheses for Knowledge Representation

In this paper, we consider decision trees that use two types of queries: queries based on one attribute each and queries based on hypotheses about values of all attributes. Such decision trees are similar to the ones studied in exact learning, where membership and equivalence queries are allowed. We...

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Bibliographic Details
Main Authors: Mohammad Azad, Igor Chikalov, Shahid Hussain, Mikhail Moshkov
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Electronics
Subjects:
knowledge representation
decision tree
hypothesis
depth
number of nodes
Online Access:https://www.mdpi.com/2079-9292/10/13/1580

Internet

https://www.mdpi.com/2079-9292/10/13/1580

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