TESTING FOR REVEALING OF DATA STRUCTURE BASED ON THE HYBRID APPROACH | Zendy

Volodymyr Mosorov | Zendy; Taras Panskyi | Zendy; Sebastian Biedroń | Zendy

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TESTING FOR REVEALING OF DATA STRUCTURE BASED ON THE HYBRID APPROACH

Author(s) -

Volodymyr Mosorov,

Taras Panskyi,

Sebastian Biedroń

Publication year - 2017

Publication title -

informatyka automatyka pomiary w gospodarce i ochronie środowiska

Language(s) - English

Resource type - Journals

eISSN - 2391-6761

pISSN - 2083-0157

DOI - 10.5604/01.3001.0010.4853

Subject(s) - cluster analysis , homogeneity (statistics) , statistic , data mining , computer science , statistical hypothesis testing , test statistic , set (abstract data type) , mathematics , statistics , artificial intelligence , machine learning , programming language

In this paper testing for revealing data structure based on a hybrid approach has been presented. The hybrid approach used during the testing suggests defining a pre-clustering hypothesis, defining a pre-clustering statistic and assuming the homogeneity of the data under pre-defined hypothesis, applying the same clustering procedure for a data set of interest, and comparing results obtained under the pre-clustering statistic with the results from the data set of interest. The pros and cons of the hybrid approach have been also considered.

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