Concept Drift Detection on financial data Using Naïve Bayes Classifier

Amadu, Hassan; Bouba, Ousmanou Mamoudou

dc.contributor.author	Amadu, Hassan
dc.contributor.author	Bouba, Ousmanou Mamoudou
dc.date.accessioned	2020-10-28T08:59:50Z
dc.date.available	2020-10-28T08:59:50Z
dc.date.issued	2019-11-15
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dc.identifier.uri	http://hdl.handle.net/123456789/606
dc.description	Supervised by Mr. Ashikur Rahman	en_US
dc.description.abstract	Concept drift detection has been a very active field of research in the domain of finance due to streaming of data which sometimes caused a significant lost to the organizations. As a result, we collected dataset for an organization and applied different machine learning algorithm to analyze the best reliable and computational comfort.	en_US
dc.language.iso	en	en_US
dc.publisher	Department of Computer Science and Engineering, Islamic University of Technology, Gazipur, Bangladesh	en_US
dc.title	Concept Drift Detection on financial data Using Naïve Bayes Classifier	en_US
dc.type	Thesis	en_US