Results 11 to 20 of about 1,054,775 (163)
HYPER HEURISTIC EVOLUTIONARY APPROACH FOR CONSTRUCTING DECISION TREE CLASSIFIERS
Journal of ICT, 2021 Decision tree models have earned a special status in predictive modeling since these are considered comprehensible for human analysis and insight.
Saroj Ratnoo +2 more
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A Two-Parameter Fractional Tsallis Decision Tree
Entropy, 2022 Decision trees are decision support data mining tools that create, as the name suggests, a tree-like model. The classical C4.5 decision tree, based on the Shannon entropy, is a simple algorithm to calculate the gain ratio and then split the attributes ...
Jazmín S. De la Cruz-García +2 more
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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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IEEE Transactions on Knowledge and Data Engineering, 2017 Uncovering causal relationships in data is a major objective of data analytics. Causal relationships are normally discovered with designed experiments, e.g. randomised controlled trials, which, however are expensive or infeasible to be conducted in many cases.
Jiuyong Li +4 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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Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison [PDF]
Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021), 2021 In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy
Jimenez-Roa, L.A. +2 more
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Classification of Images Using Decision Tree [PDF]
Engineering and Technology Journal, 2013 In this paper, the proposed system is based on texture features classification for multi object images by using decision tree (ID3) algorithm. The proposed system uses image segment tile base to reduce the block effect and uses (low low) Wavelet Haar to ...
Emad K. Jabbar, Mayada jabbar kelain
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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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, 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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