Learning ensemble of decision trees through multifactorial genetic ...
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This study utilizes the multifactorial evolution and designs a multifactorial genetic programming (MFGP) for efficiently learning an ensemble of decision trees.
This study utilizes the multifactorial evolution and designs a multifactorial genetic programming (MFGP) for efficiently learning an ensemble of decision trees.
The experimental results show that MFGP can learn an ensemble with comparable accuracy, precision, and recall to conventional ensemble learning methods, ...
The aim of this study is to propose a genetic programming (GP) based new ensemble system(named GPES), which can be used to effectively classify different types ...
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What is ensemble learning in decision tree?
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Why decision tree is prepared to use with an ensemble approach?
Such an ensemble of decision trees is called Random Forest. 4.1 Random forest. Random forest is machine learning algorithm, which consists in using an ensemble ...
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Nov 14, 2022 · In this paper, a multi-objective genetic programming (MGP) based algorithm is designed for high-performance imbalanced classification. It is ...
Missing: multifactorial | Show results with:multifactorial
Ensemble learning is a powerful paradigm that has been used in the top state-of-the-art machine learning methods like Random Forests and XGBoost.
Decision trees are deployed as base classifiers in this ensemble framework with three operators: Min, Max, and Average. Each individual of the GP is an ensemble ...
Missing: multifactorial | Show results with:multifactorial
In [17] , the authors present an approach to evolve decision trees based on GP and cellular automata. The results show that this approach has comparable (often ...
We put forward a novel learning methodology for ensembles of decision trees based on a genetic algorithm that is able to train a decision tree for maximizing ...
Missing: multifactorial | Show results with:multifactorial