Discover dependency pattern among attributes by using a new type of nonlinear multiregression

DOI10.1002/int.1043zbMath1064.68039OpenAlexW2020496369MaRDI QIDQ2747985

Zhenyuan Wang, Man-Leung Wong, Kebin Xu, Kwong-Sak Leung

Publication date: 2001

Published in: International Journal of Intelligent Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/int.1043

Mathematics Subject Classification ID

Database theory (68P15)

Related Items (5)

Modified quantum-behaved particle swarm optimization for parameters estimation of generalized nonlinear multi-regressions model based on Choquet integral with outliers ⋮ Fuzzy numbers and fuzzification of the Choquet integral ⋮ Indeterminate integrals with respect to nonadditive measures ⋮ Applying fuzzy measures and nonlinear integrals in data mining ⋮ Real-valued Choquet integrals with fuzzy-valued integrand

Cites Work

• Unnamed Item
• A genetic algorithm for determining nonadditive set functions in information fusion
• A new type of nonlinear and the computational algorithm
• Nonlinear nonnegative multiregressions based on Choquet integrals
• Choquet integrals and natural extensions of lower probabilities
• Non-monotonic fuzzy measures and the Choquet integral
• Very simple classification rules perform well on most commonly used datasets
• PFB-Integrals and PFA-Integrals with Respect to Monotone Set Functions
• PAN-INTEGRALS WITH RESPECT TO IMPRECISE PROBABILITIES
• Using genetic algorithms to determine nonnegative monotone set functions for information fusion in environments with random perturbation

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