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First, we use fuzzy sets to describe the boundaries of decision trees to generate fuzzy decision trees, and three-way classification is introduced into fuzzy decision trees, which allows data with high uncertainty to be filtered out and further considered by the users.
The objective of this study is to propose a three-way classification mechanism through incorporating fuzzy decision trees and introducing three uncertainty ...
Highlights · The aim is to form a three-way classifier based on fuzzy decision trees. · The developed mechanism could flag data with high level of uncertainty.
This study is concerned with the design of a three-way classification mechanism realized through combing fuzzy decision trees and expressing uncertainty ...
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A three-way classification with fuzzy decision trees. Abstract. This study is concerned with the design of a three-way classification mechanism realized ...
Feb 6, 2024 · This method partitions the complete decision space into three distinct regions, i.e., the positive region, the negative region, and the boundary ...
Missing: trees. | Show results with:trees.
Dec 20, 2023 · We propose a new three-way decision-making model under the hesitant fuzzy linguistic environment. The model obtains the confidence of different decision makers.
Nov 18, 2022 · This paper reviews and examines advances in three-way behavioral decision making (TW-BDM) with hesitant fuzzy information systems (HFIS)
Han [8] implemented a three-way classification mechanism by combining fuzzy decision trees with the expression of uncertainties related to classification ...
A three-way, three-valued, or three-region approximation of a fuzzy set is constructed from a pair of thresholds (α,β) on the fuzzy membership function.