Results 31 to 40 of about 6,176,379 (373)
, 2022 Recently proposed budding tree is a decision tree algorithm in which every node is part internal node and part leaf. This allows representing every decision tree in a continuous parameter space, and therefore a budding tree can be jointly trained with backpropagation, like a neural network.
Ozan İrsoy, Ethem Alpaydın
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Tree in Tree: from Decision Trees to Decision Graphs
, 2021 Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional decision tree to a more generic and powerful directed acyclic graph.
Zhu, Bingzhao, Shoaran, Mahsa
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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 ...
S. H. Yoo +11 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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Investigating Evaluation Measures in Ant Colony Algorithms for Learning Decision Tree Classifiers [PDF]
, 2015 Ant-Tree-Miner is a decision tree induction algorithm that is based on the Ant Colony Optimization (ACO) meta- heuristic. Ant-Tree-Miner-M is a recently introduced extension of Ant-Tree-Miner that learns multi-tree classification models.
Abdelbar, Ashraf M. +2 more
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Decision Tree-Based Ensemble Model for Predicting National Greenhouse Gas Emissions in Saudi Arabia
Applied Sciences, 2023 Greenhouse gas (GHG) emissions must be precisely estimated in order to predict climate change and achieve environmental sustainability in a country.
Muhammad Muhitur Rahman +7 more
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Advances in Electrical and Computer Engineering, 2014 There is a growing interest nowadays to process large amounts of data using the well-known decision-tree learning algorithms. Building a decision tree as fast as possible against a large dataset without substantial decrease in accuracy and using as ...
PURDILA, V., PENTIUC, S.-G.
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, 2015 Model tree induction is a popular method for tackling regression problems requiring interpretable models. Model trees are decision trees with multiple linear regression models at the leaf nodes.
Frank, Eibe +2 more
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Top-Down Induction of Decision Trees: Rigorous Guarantees and Inherent Limitations [PDF]
, 2019 Consider the following heuristic for building a decision tree for a function $f : \{0,1\}^n \to \{\pm 1\}$. Place the most influential variable $x_i$ of $f$ at the root, and recurse on the subfunctions $f_{x_i=0}$ and $f_{x_i=1}$ on the left and right ...
Blanc, Guy, Lange, Jane, Tan, Li-Yang
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Machine Learning Decision Tree Models for Differentiation of Posterior Fossa Tumors Using Diffusion Histogram Analysis and Structural MRI Findings. [PDF]
, 2020 We applied machine learning algorithms for differentiation of posterior fossa tumors using apparent diffusion coefficient (ADC) histogram analysis and structural MRI findings.
Aboian, Mariam +3 more
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