Del i serien Studies in Computational Intelligence

Thriving Rough Sets

10th Anniversary - Honoring Professor Zdzisław Pawlak's Life and Legacy & 35 Years of Rough Sets

Häftad, Engelska, 2018

AvGuoyin Wang,Andrzej Skowron,Yiyu Yao,Dominik Ślęzak,Lech Polkowski

1 439 kr

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This special book is dedicated to the memory of Professor Zdzislaw Pawlak, the father of rough set theory, in order to commemorate both the 10th anniversary of his passing and 35 years of rough set theory.

Produktinformation

Utgivningsdatum2018-07-25
Mått155 x 235 x 25 mm
Vikt680 g
FormatHäftad
SpråkEngelska
SerieStudies in Computational Intelligence
Antal sidor439
FörlagSpringer International Publishing AG
ISBN9783319855332

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Artificiell intelligens inom Data och IT

Part 1: Historical Review of Professor Zdzisław Pawłak and Rough Set.- The Born and Growing of Chinese Rough Set Community with Help of Professor Zdzisław Pawłak.- Zdzisław Pawłak as I Saw Him and Remember Him Now.- Recent Development of Rough Computing: A Scientometrics View.- Part 2: Review of Rough Set Research.- Rough Sets, Rough Mereology and Uncertainty.- Rough Sets in Machine Learning: A Review.- Application of Tolerance Rough Sets in Structured and Unstructured Text Categorization: A Survey.- Medical Diagnosis: Rough Set View.- Rough Set Analysis of Imprecise Classes.- Pawłak’s Many Valued Information System, Non-deterministic Information System, and a Proposal of New Topics on Information Incompleteness Toward the Actual Application.- Part 3: Rough Set Theory.- From Information Systems to Interactive Information Systems.- Back to the Beginnings: Pawłak's Definitions of the Terms Information System and Rough Set.- Knowledge and Consequence in AC Semantics for General Rough Sets.- Measuring Soft Roughness of Soft Rough Sets Induced by Covering.- Rough search of vague knowledge.- Vagueness and Uncertainty: An F-Rough Set Perspective.- Directions of Use of the Pawłak's Approach to Conflict Analysis.- Lattice Structure of Variable Precision Rough Sets.- Part 4: Rough Set Based Data Mining.- Mining for Actionable Knowledge in Tinnitus Datasets.- Rough-Granular Computing for Relational Data.- The Boosting and Bootstrap Ensembles for the Pair Classifier Based on the Dual Indiscernibility Matrix.