Results 21 to 30 of about 305,651 (314)

A Two-Parameter Fractional Tsallis Decision Tree

open access: yesEntropy, 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
doaj   +1 more source

Coding Decision Trees [PDF]

open access: yesMachine Learning, 1993
Quinlan and Rivest have suggested a decision-tree inference method using the Minimum Description Length idea. We show that there is an error in their derivation of message lengths, which fortunately has no effect on the final inference. We further suggest two improvements to their coding techniques, one removing an inefficiency in the description of ...
Chris S. Wallace, Jon D. Patrick
openaire   +2 more sources

Permutation Decision Trees

open access: yesCoRR, 2023
15 pages, 8 ...
B, Harikrishnan N   +2 more
openaire   +2 more sources

Decision-tree.

open access: yes, 2022
Decision-tree.
Janne C. Mewes (6623033)   +2 more
core   +2 more sources

Distributed Decision Trees

open access: yes, 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 Irsoy, Ethem Alpaydin
openaire   +3 more sources

HYPER HEURISTIC EVOLUTIONARY APPROACH FOR CONSTRUCTING DECISION TREE CLASSIFIERS

open access: yesJournal 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
doaj   +3 more sources

Contextual Decision Trees

open access: yesCoRR, 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
openaire   +2 more sources

Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]

open access: yes, 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

Achieving Verifiable Decision Tree Prediction on Hybrid Blockchains

open access: yesEntropy, 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
doaj   +1 more source

Decision Tree-Based Ensemble Model for Predicting National Greenhouse Gas Emissions in Saudi Arabia

open access: yesApplied 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
doaj   +1 more source

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