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The selection of an appropriate method of data analysis is a key problem for researchers from various fields of applications. They consider different methods of data classification,often based on the thematic scope of the data at their disposal.However, various data characteristics, such as data set size, datatype and quality, gaps, outliers and other anomalies, can makeproper selection significantly difficult. Therefore, in this study wepropose a method based on a very universal classifier designedon the basis of calculations using information granules. The mainobjective of the work is to present and comprehensively verifythe effectiveness of the classifier. As an example of application,we propose complicated yet currently important data comingfrom widely understood ecological research. Detailed numerical experiments indicate the high efficiency of the proposed methodand the possibility of easy application to data appearing in otherfields. In addition, various types of aggregation functions of theclassification results are considered in order to obtain the mostreliable results for the discussed problems.
