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SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules
arXiv.orgBayesian Additive Regression Trees [BART, Chipman et al., 2010] have gained significant popularity due to their remarkable predictive performance and ability to quantify uncertainty. However, standard decision tree models rely on recursive data splits at
Stamatina Lamprinakou+3 more
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Decision Trees for the Imputation of Categorical Data
, 2017Resolving the problem of missing data via imputation can theoretically be done by any prediction model. In the field of machine learning, a well known type of prediction model is a decision tree. However, the literature on how suitable a decision tree is
Tobias Rockel, D. Joenssen, U. Bankhofer
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GATree: Evolutionary decision tree classifier in Python
Journal of Open Source SoftwareGATree is a Python library that simplifies the way decision trees are constructed and optimised for classification machine learning tasks 1 . Leveraging the principles of standard genetic algorithms, GATree allows for the dynamic evolution of decision ...
Tadej Lahovnik, Sašo Karakatič
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Comparative Analysis of Deterministic and Nondeterministic Decision Trees
Intelligent Systems Reference Library, 2020M. Moshkov
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Counting the Number of Perfect Matchings, and Generalized Decision Trees
Problems of Information Transmission, 2021Mikhail N. Vyalyi
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Proof complexity of systems of (non-deterministic) decision trees and branching programs
Sam Buss, Anupam Das, Alexander Knop
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Decision trees unearth return sign predictability in the S&P 500
, 2018L. Fievet, D. Sornette
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Using similarity-based selection in evolutionary design of decision trees
International Convention on Information and Communication Technology, Electronics and Microelectronics, 2015Leon Bošnjak+2 more
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COMPARITIVE ANALYSIS OF DETERMINISTIC AND NONDETERMINISTIC DECISION TREE COMPLEXITY. GLOBAL APPROACH
Mikhail Moshkov
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