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EVALUATION OF DECISION TREE TECHNIQUES
1
Author(s):
SAVITA
Vol - 9, Issue- 1 ,
Page(s) : 89 - 95
(2019 )
DOI : https://doi.org/10.32804/RJSET
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Abstract
An important issue in the KDD process is the development of efficient indicators for assessing the quality of the analysis results. The fundamental aspect of machine learning is to evaluate the performance of a classification tree. After receiving the training set as input the decision tree inducer can construct classification tree which can classify an unseen instances. Evaluation criteria is used to evaluate the classification tree and the inducer both. It is very important to evaluate the classification tree to understand the quality of it and for refining the parameters in the KDD iterative process.
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