Toward a language for specifying summarizing statistics

Authors:
R. R. Yager
Affiliations:
Machine Intelligence Inst., New Rochelle, NY, USA
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2003

Citing 0
Cited 4

A granular extension of the fuzzy-ARTMAP (FAM) neural classifier based on fuzzy lattice reasoning (FLR)

Neurocomputing
Linguistic Summary-Based Query Answering on Data Cubes with Time Dimension

FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
Fuzzy quantification-based linguistic summaries in data cubes with hierarchical fuzzy partition of time dimension

IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Time series comparison using linguistic fuzzy techniques

IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty

Quantified Score

Hi-index	0.00

Visualization

Abstract

We introduce the ordered weighted averaging (OWA) operator and discuss how it can provide a basis for generating summarizing statistics over large data sets. We further note how different forms of OWA operators can be induced using weight generating functions. We show how these weight generating functions can provide a vehicle with which a data analyst can express desired summarizing statistics. Our goal is to develop an understanding of the relationship between weight generating functions and resulting summarizing statistics.