NDLI: Design and Analysis of an Efficient Multi-Relational Decision Tree Learning Algorithm

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Design and Analysis of an Efficient Multi-Relational Decision Tree Learning Algorithm

Content Provider	Scilit
Author	Yadav, Chhutten Singh Kumar, Abhishek Kumar, Ankit Dadheech, Pankaj
Copyright Year	2021
Description	Journal: Iop Conference Series: Materials Science and Engineering In today’s day of modern era when the data handling objectives are getting bigger and bigger with respect to volume, learning and inferring knowledge from complex data becomes the utmost problem. The research in Knowledge Discovery in Databases has been primarily directed to attribute-value learning in which one is described through a fixed set tuple given with their values. Database or dataset is seen in the form of table relation in which every row corresponds to an instance and column represents an attribute respectively. In this paper a New framework is introduced a much more sophisticated and deserving approach i.e., Hybrid Multi-Relational Decision Tree Learning Algorithm which overcomes with Exiting technology drawbacks and other anomalies. Result show that Hybrid Multi- Relational Decision Tree Learning Algorithm provides certain methods which reduces its execution time. Experimental results on different datasets provide a clear indication that Hybrid Multi-Relational Decision Tree Learning Algorithm is comprehensively a better approach.
Related Links	https://iopscience.iop.org/article/10.1088/1757-899X/1099/1/012075/pdf
ISSN	17578981
e-ISSN	1757899X
DOI	10.1088/1757-899x/1099/1/012075
Journal	Iop Conference Series: Materials Science and Engineering
Issue Number	1
Volume Number	1099
Language	English
Publisher	IOP Publishing
Publisher Date	2021-03-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Materials Science and Engineering Cybernetical Science Multi Relational Decision Relational Decision Tree Learning Algorithm Decision Tree Learning
Content Type	Text
Resource Type	Article

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