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A new approach to drawing conclusions from data. A rough set perspective

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TLDR
The presented approach has found many real-life applications and it seems that can be used in some kind of legal reasoning.
Abstract
Rough set theory is a new mathematical approach to vague and uncertain data analysis. The paper explains basic concepts of the theory and outlines briefly applications of the method to drawing conclusions from factual data. The presented approach has found many real-life applications and it seems that can be used in some kind of legal reasoning.

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References
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Book

Rough-Fuzzy Hybridization: A New Trend in Decision Making

TL;DR: This volume provides a collection of twenty articles containing new material and describing the basic concepts and characterizing features of rough set theory and its integration with fuzzy set theory, for developing an efficient soft computing strategy of machine learning.
Book

New directions in rough sets, data mining, and granular-soft computing, 7th International Workshop, RSFDGrC'99, Yamaguchi, Japan, November 9-11, 1999 : proceedings

TL;DR: In this article, Rough Set Theory and its applications have been explored in the context of data mining and knowledge discovery, including the use of Rough Set theory for finding equivalence relations from tables with non-deterministic information.
BookDOI

New Directions in Rough Sets, Data Mining, and Granular-Soft Computing

TL;DR: In this article, Rough Set Theory and its applications have been explored in the context of data mining and knowledge discovery, including the use of Rough Set theory for finding equivalence relations from tables with non-deterministic information.
Book

Fundamentals of the New Artificial Intelligence: Beyond Traditional Paradigms

TL;DR: Introduction.