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IMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI PRODUK LARIS
JURNAL ILMIAH ILMU KOMPUTER, 2021 Decision Tree C4.5 algorithm is an algorithm that can be used to make a decision tree. Decision tree (Decision Tree) is one method that is quite easily interpreted by humans.
Asmaul Husnah Nasrullah
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Omnivariate decision trees [PDF]
IEEE Transactions on Neural Networks, 2001 Univariate decision trees at each decision node consider the value of only one feature leading to axis-aligned splits. In a linear multivariate decision tree, each decision node divides the input space into two with a hyperplane. In a nonlinear multivariate tree, a multilayer perceptron at each node divides the input space arbitrarily, at the expense ...
Olcay Taner Yildiz, Ethem Alpaydin
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CoRR, 2022 Focusing on Random Forests, we propose a multi-armed contextual bandit recommendation framework for feature-based selection of a single shallow tree of the learned ensemble. The trained system, which works on top of the Random Forest, dynamically identifies a base predictor that is responsible for providing the final output.
Tommaso Aldinucci +3 more
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SDTR: Soft Decision Tree Regressor for Tabular Data
IEEE Access, 2021 Deep neural networks have been proved a success in multiple fields. However, researchers still favor traditional approaches to obtain more interpretable models, such as Bayesian methods and decision trees when processing heterogeneous tabular data.
Hao-Ran Luo, Fan Cheng, Heng Yu, Yuqi Yi
semanticscholar +1 more source
SAT-based Decision Tree Learning for Large Data Sets
AAAI Conference on Artificial Intelligence, 2021 Decision trees of low depth are beneficial for understanding and interpreting the data they represent. Unfortunately, finding a decision tree of lowest depth that correctly represents given data is NP-hard.
André Schidler, Stefan Szeider
semanticscholar +1 more source
Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]
, 2014 Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the ...
Marcin Czajkowski +5 more
core +1 more source
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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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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Orthogonal decision trees [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2006 This paper introduces orthogonal decision trees that offer an effective way to construct a redundancy-free, accurate, and meaningful representation of large decision-tree-ensembles often created by popular techniques such as bagging, boosting, random forests, and many distributed and data stream mining algorithms.
Hillol Kargupta +2 more
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Ilkom Jurnal Ilmiah, 2023 The global impact of the COVID-19 pandemic has been profound, affecting economies and societal structures worldwide. Indonesia, with a high caseload, has encountered significant challenges across various sectors.
Bhima Satria Rizki Sugiono +4 more
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