Predictive tools in data mining and \(k\)-means clustering: universal inequalities
DOI10.1007/s00025-012-0233-2zbMath1285.60014OpenAlexW2027961837MaRDI QIDQ351072
Hamzeh Agahi, Seiyed Mansour Vaezpour, Adel Mochammadpour
Publication date: 11 July 2013
Published in: Results in Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00025-012-0233-2
Jensen's inequalitydata miningHölder's inequalityChebyshev's inequalityLyapunov's inequalityMinkowski's inequalitymonotone measureuniversal integralStolarsky's inequality
Inequalities; stochastic orderings (60E15) Functional inequalities, including subadditivity, convexity, etc. (39B62)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- General Chebyshev type inequalities for universal integral
- On fuzzy equivalence. II
- General Chebyshev type inequalities for Sugeno integrals
- On the Chebyshev type inequality for seminormed fuzzy integral
- An inequality related to Minkowski type for Sugeno integrals
- New general extensions of Chebyshev type inequalities for Sugeno integrals
- Hölder type inequality for Sugeno integral
- Two families of fuzzy integrals
- Two integrals and some modified versions - critical remarks
- Pseudo-additive measures and integrals
- Triangular norms
- On non-additive probabilistic inequalities of Hölder-type
- Relations among univariate aging, bivariate aging and dependence for exchangeable lifetimes
- Choquet-like integrals
- Fuzzy measures and integrals. Theory and applications
- General Minkowski type inequalities for Sugeno integrals
- Fuzzy integrals and linearity
- Fuzzy Chebyshev type inequality
- A Jensen type inequality for fuzzy integrals
- A Chebyshev type inequality for fuzzy integrals
- ON AN EXTENDED CHEBYSHEV TYPE INEQUALITY FOR SEMI(CO)NORMED FUZZY INTEGRALS
- A Nonlinear Integral Which Generalizes Both the Choquet and the Sugeno Integral
- DOMINATION OF AGGREGATION OPERATORS AND PRESERVATION OF TRANSITIVITY
This page was built for publication: Predictive tools in data mining and \(k\)-means clustering: universal inequalities