Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings [PDF]
Frontiers in Oncology, 2020 We applied machine learning algorithms for differentiation of posterior fossa tumors using apparent diffusion coefficient (ADC) histogram analysis and structural MRI findings.
Seyedmehdi Payabvash +5 more
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Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains
Entropy, 2023 Machine learning has become increasingly popular in academic and industrial communities and has been widely implemented in various online applications due to its powerful ability to analyze and use data.
Moxuan Fu +5 more
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Pembentukan Model Pohon Keputusan pada Database Car Evaluation Menggunakan Statistik Chi-Square
Contemporary Mathematics and Applications (ConMathA), 2022 The study discusses problems related to the formation of a decision tree based on a collection of evaluation data records obtained from a number of car buyers. This secondary data was obtained from the UCL machine learning website.
Retno Maharesi
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Study on Adaptive Bitrate Algorithm in Decision Tree Based on Imitation Learning [PDF]
Jisuanji gongcheng, 2023 Adaptive Bitrate（ABR） algorithm is an effective method to improve the quality of streaming media services，mainly divided into heuristic and learning-based algorithms.The traditional heuristic algorithm is based on fixed rules，making it difficult to ...
WANG Bo, ZHANG Yuan, YANG Yongbei
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Heat demand prediction: A real-life data model vs simulated data model comparison
Energy Reports, 2021 In the recent years machine learning algorithms have developed further and various applications are taking advantage of this advancement. Modern machine learning is now used in district heating for more precise and realistic heat demand prediction ...
Kevin Naik, Anton Ianakiev
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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
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Deep Learning-Based Decision-Tree Classifier for COVID-19 Diagnosis From Chest X-ray Imaging
Frontiers in Medicine, 2020 The global pandemic of coronavirus disease 2019 (COVID-19) has resulted in an increased demand for testing, diagnosis, and treatment. Reverse transcription polymerase chain reaction (RT-PCR) is the definitive test for the diagnosis of COVID-19; however ...
Seung Hoon Yoo +11 more
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TNT: An Interpretable Tree-Network-Tree Learning Framework using Knowledge Distillation
Entropy, 2020 Deep Neural Networks (DNNs) usually work in an end-to-end manner. This makes the trained DNNs easy to use, but they remain an ambiguous decision process for every test case.
Jiawei Li +5 more
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Computers and Education: Artificial Intelligence, 2021 In the area of machine learning and data science, decision tree learning is considered as one of the most popular classification techniques. Therefore, a decision tree algorithm generates a classification and predictive model, which is simple to ...
Vasiliki Matzavela, Efthimios Alepis
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On Laws of Thought—A Quantum-like Machine Learning Approach
Entropy, 2023 Incorporating insights from quantum theory, we propose a machine learning-based decision-making model, including a logic tree and a value tree; a genetic programming algorithm is applied to optimize both the logic tree and value tree.
Lizhi Xin, Kevin Xin, Houwen Xin
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