Decision Rules Derived from Optimal Decision Trees with Hypotheses
Entropy, 2021 Conventional decision trees use queries each of which is based on one attribute. In this study, we also examine decision trees that handle additional queries based on hypotheses.
Mohammad Azad +4 more
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A Novel Ensemble Framework for Comprehensive Early-Stage Colorectal Cancer Diagnosis, Prognosis, and Treatment: Integration of Gastroenterology-Specific Transformer Language Models and Multiple Decision Trees. [PDF]
J Clin MedSimsek C, Ucdal M, Yalcin S, Karakoc D.
europepmc +3 more sources
Predicting Credit Scores with Boosted Decision Trees
Forecasting, 2022 Credit scoring models help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a ...
João A. Bastos
doaj +1 more source
Evolutionary Learning of Interpretable Decision Trees
IEEE Access, 2023 In the last decade, reinforcement learning (RL) has been used to solve several tasks with human-level performance. However, there is a growing demand for interpretable RL, i.e., there is the need to understand how a RL agent works and the rationale of ...
Leonardo L. Custode, Giovanni Iacca
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Decision trees for regular factorial languages
Array, 2022 In this paper, we study arbitrary regular factorial languages over a finite alphabet Σ. For the set of words L(n)of the length n belonging to a regular factorial language L, we investigate the depth of decision trees solving the recognition and the ...
Mikhail Moshkov
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FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees [PDF]
Judgment and Decision Making, 2017 Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily ...
Nathaniel D. Phillips +3 more
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Optimization of decision trees using modified African buffalo algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Decision tree induction is a simple, however powerful learning and classification tool to discover knowledge from the database. The volume of data in databases is growing to quite large sizes, both in the number of attributes and instances.
Archana R. Panhalkar, Dharmpal D. Doye
doaj +1 more source
A Bi-criteria optimization model for adjusting the decision tree parameters
Kuwait Journal of Science, 2022 Decision trees play a very important role in knowledge representation because of its simplicity and self-explanatory nature. We study the optimization of the parameters of the decision trees to find a shorter as well as more accurate decision tree ...
Mohammad Azad, Mikhail Moshkov
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Practical Federated Gradient Boosting Decision Trees [PDF]
AAAI Conference on Artificial Intelligence, 2019 Gradient Boosting Decision Trees (GBDTs) have become very successful in recent years, with many awards in machine learning and data mining competitions. There have been several recent studies on how to train GBDTs in the federated learning setting.
Q. Li, Zeyi Wen, Bingsheng He
semanticscholar +1 more source
Improved Random Forest Algorithm Based on Out-of-Bag Prediction and Extended Space [PDF]
Jisuanji gongcheng, 2022 On the basis of the bootstrap method, the random forest algorithm constructs a decision tree by using sampling characteristics.This reduces the correlation among decision trees at the expense of decision tree accuracy, thereby improving the prediction ...
CHANG Shuo, ZHANG Yanchun
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