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Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03107391" target="_blank" >RIV/68407700:21230/04:03107391 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Anachronistic Attributes in Temporal Data: A Case Study

Popis výsledku v původním jazyce

The paper concerns mining data lacking the uniform structure. The data are collected from a number of objects during repeated measurements, all of which are tagged by a corresponding time. No attribute-valued machine learning algorithm can be applied directly on such data since the number of measurements is not fixed but it varies. The available data have to be transformed and preprocessed in such a way that a uniform type of information is obtained about all the considered objects. This can be achieved, e.g., by aggregation. But this process can introduce anachronistic variables, i.e., variables containing information which cannot be available at the moment when a prediction is needed. The paper suggests and tests a method how to preprocess the considered type of data without falling into a trap of introducing anachronistic attributes. The method is illustrated on a case study based on STULONG data.

Název v anglickém jazyce

Anachronistic Attributes in Temporal Data: A Case Study

Popis výsledku anglicky

The paper concerns mining data lacking the uniform structure. The data are collected from a number of objects during repeated measurements, all of which are tagged by a corresponding time. No attribute-valued machine learning algorithm can be applied directly on such data since the number of measurements is not fixed but it varies. The available data have to be transformed and preprocessed in such a way that a uniform type of information is obtained about all the considered objects. This can be achieved, e.g., by aggregation. But this process can introduce anachronistic variables, i.e., variables containing information which cannot be available at the moment when a prediction is needed. The paper suggests and tests a method how to preprocess the considered type of data without falling into a trap of introducing anachronistic attributes. The method is illustrated on a case study based on STULONG data.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2004

Kód důvěrnosti údajů

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

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

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Svazek periodika

14

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

14

Strana od-do

421-434

Kód UT WoS článku

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EID výsledku v databázi Scopus

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