Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science
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Published By Springer International Publishing

9783319975467, 9783319975474

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Measures of Dispersion for Interval Data

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_13 ◽

2018 ◽

pp. 91-98 ◽

Cited By ~ 1

Author(s):

Przemyslaw Grzegorzewski

Keyword(s):

Interval Data ◽

Measures Of Dispersion

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Monitoring of Time Series Using Fuzzy Weighted Prediction Models

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_15 ◽

2018 ◽

pp. 107-114 ◽

Cited By ~ 2

Author(s):

Olgierd Hryniewicz ◽

Katarzyna Kaczmarek-Majer

Keyword(s):

Time Series ◽

Prediction Models

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Generalising the Pari-Mutuel Model

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_28 ◽

2018 ◽

pp. 216-223

Author(s):

Chiara Corsato ◽

Renato Pelessoni ◽

Paolo Vicig

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Continuity of the Shafer-Vovk-Ville Operator

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_26 ◽

2018 ◽

pp. 200-207 ◽

Cited By ~ 1

Author(s):

Natan T’Joens ◽

Gert de Cooman ◽

Jasper De Bock

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Beyond Doss and Fréchet Expectation Sets

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_24 ◽

2018 ◽

pp. 183-190

Author(s):

Juan Jesus Salamanca

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Compatibility, Coherence and the RIP

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_22 ◽

2018 ◽

pp. 166-174

Author(s):

Enrique Miranda ◽

Marco Zaffalon

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Z-numbers as Generalized Probability Boxes

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_10 ◽

2018 ◽

pp. 68-77

Author(s):

Didier Dubois ◽

Henri Prade

Keyword(s):

Generalized Probability

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Some Partial Order Relations on a Set of Random Variables

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_6 ◽

2018 ◽

pp. 42-45

Author(s):

Bernard De Baets ◽

Hans De Meyer

Keyword(s):

Partial Order ◽

Random Variables ◽

Order Relations

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Density Estimation with Imprecise Kernels: Application to Classification

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_9 ◽

2018 ◽

pp. 59-67

Author(s):

Guillaume Dendievel ◽

Sebastien Destercke ◽

Pierre Wachalski

Keyword(s):

Density Estimation

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A Maximum Likelihood Approach to Inference Under Coarse Data Based on Minimax Regret

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science ◽

10.1007/978-3-319-97547-4_14 ◽

2018 ◽

pp. 99-106 ◽

Cited By ~ 1

Author(s):

Romain Guillaume ◽

Didier Dubois

Keyword(s):

Maximum Likelihood ◽

Minimax Regret ◽

Maximum Likelihood Approach ◽

Likelihood Approach ◽

Coarse Data

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Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Measures of Dispersion for Interval Data

Monitoring of Time Series Using Fuzzy Weighted Prediction Models

Generalising the Pari-Mutuel Model

Continuity of the Shafer-Vovk-Ville Operator

Beyond Doss and Fréchet Expectation Sets

Compatibility, Coherence and the RIP

Z-numbers as Generalized Probability Boxes

Some Partial Order Relations on a Set of Random Variables

Density Estimation with Imprecise Kernels: Application to Classification

A Maximum Likelihood Approach to Inference Under Coarse Data Based on Minimax Regret

Advances in Intelligent Systems and Computing - Uncertainty Modelling in Data Science
Latest Publications