Synthetic data generator for testing of classification rule algorithms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F26441021%3A_____%2F17%3AN0000015" target="_blank" >RIV/26441021:_____/17:N0000015 - isvavai.cz</a>
Result on the web
<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>

Result language
angličtina
Original language name
Synthetic data generator for testing of classification rule algorithms
Original language description
We developed a data generating system that is able to create systematically testing datasets that accomplish user’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.
Czech name
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Czech description
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Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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