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It is an ensemble classifier methodology based on decision trees.
However, a decision model based on decision trees exponentially grows with inspection and maintenance number.
The proposed method involves the fusion of classifiers based on decision trees designed using fuzzy techniques.
Actually, the method used to build If-Then regression rules in this work is based on decision trees [30].
Using the new proposed hybrid algorithms based on decision trees enhanced the simple MLP and RBF models' performance.
Ahadi, Lister, Haapala, and Vihavainen, (2015) outline a promising classifier (based on decision trees) approach to predicting low-performing and high-performing programming students.
Similar(38)
The proposed approach is based on decision tree and artificial bee colony.
Here, all boosting methods are based on decision tree for the comparison of performance.
The proposed ABBDT approach is based on decision tree and artificial bee colony (ABC).
And then, AdaBoost algorithm based on decision tree is utilized to confirm the idea of boosting algorithm.
The classification process based on decision tree algorithm starts at the root of the tree and proceeds to a leaf, which indicates the classification output [52].
More suggestions(22)
based on attack trees
based on requirement trees
based on mutagenetic trees
based on gateway trees
based on decision algorithms
based on building trees
based on vehicle trees
based on requirement trees
based on family trees
based on gene trees
based on decision types
based on suffix trees
based on syntax trees
based on interaction trees
based on view trees
based on regression trees
based on classification trees
based on divergence trees
based on attack trees
based on gateway trees
based on decision rules
basis on decision trees
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