SYNTHETIC DATA GENERATOR FOR TESTING OF CLASSIFICATION RULE ALGORITHMS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F17%3A43914967" target="_blank" >RIV/60461373:22340/17:43914967 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.nnw.cz/doi/2017/NNW.2017.27.010.pdf" target="_blank" >http://www.nnw.cz/doi/2017/NNW.2017.27.010.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/NNW.2017.27.010" target="_blank" >10.14311/NNW.2017.27.010</a>

Jazyk výsledku

angličtina

Název v původním jazyce

SYNTHETIC DATA GENERATOR FOR TESTING OF CLASSIFICATION RULE ALGORITHMS

Popis výsledku v původním jazyce

We developed a data generating system that is able to create systematically testing datasets that accomplish user&apos;s requirements such as number of rows, number and type of attributes, number of missing values, class noise and imbalance ratio. These datasets can be used for testing of the algorithms designed for solving classification rule problem. We used them for optimizing of the parameters of the classification algorithm based on the behavior of ant colonies. But they can be advantageously used for other applications too. Program generates output files in ARFF format. Two standards and one user-define probability distributions are used in data generation: uniform distribution, normal distribution and irregular distribution for nominal attributes. To our knowledge, our system is probably the first synthetic data generation system that systematically generates datasets for examination and judgment of the classification rule algorithms.

Název v anglickém jazyce

SYNTHETIC DATA GENERATOR FOR TESTING OF CLASSIFICATION RULE ALGORITHMS

Popis výsledku anglicky

We developed a data generating system that is able to create systematically testing datasets that accomplish user&apos;s requirements such as number of rows, number and type of attributes, number of missing values, class noise and imbalance ratio. These datasets can be used for testing of the algorithms designed for solving classification rule problem. We used them for optimizing of the parameters of the classification algorithm based on the behavior of ant colonies. But they can be advantageously used for other applications too. Program generates output files in ARFF format. Two standards and one user-define probability distributions are used in data generation: uniform distribution, normal distribution and irregular distribution for nominal attributes. To our knowledge, our system is probably the first synthetic data generation system that systematically generates datasets for examination and judgment of the classification rule algorithms.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

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

—

Svazek periodika

27

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

15

Strana od-do

215-229

Kód UT WoS článku

000402020800003

EID výsledku v databázi Scopus

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