Autor:

Zhong, Ning ; Skowron, Andrzej

Współtwórca:

Grzymala-Busse, Jerzy - ed. ; Świniarski, Roman W. - ed. ; Zhong, Ning - ed. ; Ziarko, Wojciech - ed.

Tytuł:

A rough set-based knowledge discovery process

Podtytuł:

Rough Sets and Their Applications

Tytuł publikacji grupowej:

AMCS, volume 11 (2001)

Temat i słowa kluczowe:

rough sets ; KDD process ; hybrid systems

Abstract:

The knowledge discovery from real-life databases is a multi-phase process consisting of numerous steps, including attribute selection, discretization of real-valued attributes, and rule induction. In the paper, we discuss a rule discovery process that is based on rough set theory. ; The core of the process is a soft hybrid induction system called the Generalized Distribution Table and Rough Set System (GDT-RS) for discovering classification rules from databases with uncertain and incomplete data. The system is based on a combination of Generalization Distribution Table (GDT) and the Rough Set methodologies. ; In the preprocessing, two modules, i.e. Rough Sets with Heuristics (RSH) and Rough Sets with Boolean Reasoning (RSBR), are used for attribute selection and discretization of real-valued attributes, respectively. We use a slope-collapse database as an example showing how rules can be discovered from a large, real-life database.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2001

Typ zasobu:

artykuł

Strony:

603-619

Źródło:

AMCS, volume 11, number 3 (2001) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

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Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego