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Gasparoviča-Asīte, M; Aleksejeva, L; Gersons, V (2012)
Publisher: RTU Izdevniecība
Languages: English
Types: Conference object
Subjects: Classification algorithms, bioinformatics data, BEXA, UCI data.

Classified by OpenAIRE into

ACM Ref: ComputingMethodologies_PATTERNRECOGNITION
This article studies the possibilities of BEXA family classification algorithms – BEXA, FuzzyBexa and FuzzyBexa II in data, especially bioinformatics data, classification. Three different types of data sets were used in the study – data sets often used in the literature (like Iris data set), UCI data repository real life data sets (like breast cancer data set) and real bioinformatics data sets that have the specific character – a large number of attributes (several thousands) and a small number of records. For the comparison of classification results experiments were carried out using all data sets and other classification algorithms. As a result, conclusions were drawn and recommendations given about the use of each algorithm of BEXA family for classification of various real data, as well as an answer is given to the question, whether the use of these algorithms is recommended for bioinformatics data.

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