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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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On Decision Trees, Influences, and Learning Monotone Decision Trees
, 2004 In this note we prove that a monotone boolean function computable by a decision tree of size s has average sensitivity at most √ log2 s. As a consequence we show that monotone functions are learnable to constant accuracy under the uniform distribution in time polynomial in their decision tree size.
Ryan O’Donnell, Rocco A. Servedio
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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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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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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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Learning stochastic decision trees
, 2021 We give a quasipolynomial-time algorithm for learning stochastic decision trees that is optimally resilient to adversarial noise. Given an $ $-corrupted set of uniform random samples labeled by a size-$s$ stochastic decision tree, our algorithm runs in time $n^{O(\log(s/\varepsilon)/\varepsilon^2)}$ and returns a hypothesis with error within an ...
Blanc, Guy, Lange, Jane, Tan, Li-Yang
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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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Discrimination Aware Decision Tree Learning [PDF]
2010 IEEE International Conference on Data Mining, 2010 Recently, the following problem of discrimination aware classification was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B.
Kamiran, F. +2 more
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