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HHCART: An oblique decision tree [PDF]
Computational Statistics & Data Analysis, 2016 Decision trees are a popular technique in statistical data classification. They recursively partition the feature space into disjoint sub-regions until each sub-region becomes homogeneous with respect to a particular class. The basic Classification and Regression Tree (CART) algorithm partitions the feature space using axis parallel splits.
Darshana Chitraka Wickramarachchi +4 more
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CoRR, 2013 This paper describes experiments, on two domains, to investigate the effect of averaging over predictions of multiple decision trees, instead of using a single tree. Other authors have pointed out theoretical and commonsense reasons for preferring the multiple tree approach.
Suk Wah Kwok, Chris Carter
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Saúde em DebateObjetivou-se desenvolver um modelo de apoio à tomada de decisão para identificar indivíduos não aderentes ao tratamento anti-hipertensivo. Propõe-se a utilização de árvore de decisão sobre um banco de dados de adesão ao tratamento envolvendo 118 usuários
Amira Rose Costa Medeiros +3 more
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An anonymization technique using intersected decision trees
Journal of King Saud University: Computer and Information Sciences, 2015 Data mining plays an important role in analyzing the massive amount of data collected in today’s world. However, due to the public’s rising awareness of privacy and lack of trust in organizations, suitable Privacy Preserving Data Mining (PPDM) techniques
Sam Fletcher, Md Zahidul Islam
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Building decision trees based on production knowledge as support in decision-making process
Production Engineering Archives, 2020 The article presents sources of production knowledge and thoroughly describes its identification which on the construction of decision trees, and on the construction of knowledge bases for production processes.
Matuszny Marcin
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A New Algorithm for Optimization of Fuzzy Decision Tree in Data Mining [PDF]
Journal of Optimization in Industrial Engineering, 2011 Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility.
Abolfazl Kazemi, Elahe Mehrzadegan
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CoRRNeurosymbolic (NeSy) AI studies the integration of neural networks (NNs) and symbolic reasoning based on logic. Usually, NeSy techniques focus on learning the neural, probabilistic and/or fuzzy parameters of NeSy models. Learning the symbolic or logical structure of such models has, so far, received less attention.
Matthias Möller +3 more
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A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design
IEEE Access, 2019 Decision trees are an extremely popular machine learning technique. Unfortunately, overfitting in decision trees still remains an open issue that sometimes prevents achieving good performance.
Rafael Garcia Leiva +3 more
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Shopping intention prediction using decision trees
Millenium, 2017 Introduction: The price is considered to be neglected marketing mix element due to the complexity of price management and sensitivity of customers on price changes. It pulls the fastest customer reactions to that change.
Dario Šebalj +2 more
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