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dc.contributor.authorBramer, Maxen_US
dc.date.accessioned2020-08-05T07:12:46Z
dc.date.available2020-08-05T07:12:46Z
dc.date.issued2016en_US
dc.identifier.isbn978-1-4471-7306-9en_US
dc.identifier.isbn978-1-4471-7307-6en_US
dc.identifier.otherHPU2164623en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/33702
dc.description.abstractThis book explains and explores the principal techniques of Data Mining, the automatic extraction of implicit and potentially useful information from data, which is increasingly used in commercial, scientific and other application areas. It focuses on classification, association rule mining and clustering. Each topic is clearly explained, with a focus on algorithms not mathematical formalism, and is illustrated by detailed worked examples. The book is written for readers without a strong background in mathematics or statistics and any formulae used are explained in detail. It can be used as a textbook to support courses at undergraduate or postgraduate levels in a wide range of subjects including Computer Science, Business Studies, Marketing, Artificial Intelligence, Bioinformatics and Forensic Science. As an aid to self study, this book aims to help general readers develop the necessary understanding of what is inside the 'black box' so they can use commercial data mining packages discriminatingly, as well as enabling advanced readers or academic researchers to understand or contribute to future technical advances in the field.en_US
dc.format.extent530p.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectData Miningen_US
dc.subjectAlgorithmsen_US
dc.subjectComputer Scienceen_US
dc.titlePrinciples of Data Mining (3 ed.)en_US
dc.typeBooken_US
dc.size3,86 MBen_US
dc.departmentTechnologyen_US


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