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Knowledge Extraction from Inductive Models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F05%3A03115273" target="_blank" >RIV/68407700:21230/05:03115273 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Knowledge Extraction from Inductive Models

  • Original language description

    The task of critical importance is to extract knowledge from an inductive model, once it was built. There are several techniques that can be used for this purpose. Some of them are well known (e.g. generating of math formula from a model) and some of them are to be introduced in this paper. Knowledge extraction (of the system modelled) by means of visualisation of its behaviour for both regression and classification problems will be described. Two methods telling us how to derive feature ranking from inductive model conclude the paper.

  • Czech name

    Není k dispozici

  • Czech description

    Není k dispozici

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2005

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the International Workshop on Inductive Modeling IWIM-2005

  • ISBN

    966-02-3734-0

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    37-44

  • Publisher name

    Akademie věd Ukrajiny, ústav kybernetiky V.M.Gluškova

  • Place of publication

    Kyjev

  • Event location

    Kyjev

  • Event date

    Jul 11, 2005

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article