2023
DOI: 10.59287/as-abstracts.1202
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Improving Random Forest with Pre-pruning technique for Binary classification

Abstract: Random Forest (RF) is a popular machine learning algorithm. It is based on the concept of ensemble learning, which is a process of combining several classifiers to solve a complex problem and improve model performance. The random forest allows extending the notions of decision trees (DT) in order to build more stable models. In this work we propose to further improve the predictions of the trees in the forest by a pre-pruning technique, which aims to optimize the performance of the nodes and to minimize the si… Show more

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