A Comparative Study of Various Multi Relational Decision Tree Learning Algorithms

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Provided by: International Journal of Engineering Research and Development (IJERD)
Topic: Data Management
Format: PDF
In this paper, the authors provide an introduction and insight into the family of multi-relational decision tree learning algorithms by providing the comparative study. This paper will be a great help for those who wish to perceive their career in the area of relational decision tree induction. After the comparative study, it provides an improved version of the MRDTL (Multi-Relational Decision Tree Learning) algorithm that proposes the use of the tuple ID propagation instead of the complex data structures such as selection graph as are employed in the older generation of the algorithms.
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