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dc.contributor.editorRybarczyk, Yves
dc.date.accessioned2024-07-11T07:54:00Z
dc.date.available2024-07-11T07:54:00Z
dc.date.issued2024
dc.identifierONIX_20240711_9781837690794_75
dc.identifier.issn2633-1403
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/140261
dc.description.abstractFor contemporary societies, data mining has emerged as a serious challenge. Thanks to more advanced analytical tools, the Big Data explosion has enabled businesses to assess their performance more thoroughly and accurately. For example, transitioning from using a basic spreadsheet to using data lake modeling offers more flexibility in terms of consulting and summarizing vast amounts of data from many business angles. Data mining, which is the foundation for this optimization of data analysis, has been strengthened by artificial intelligence and machine learning to find patterns in this deluge of data and build future prediction models, turning it into a critical tool for decision-making. This book provides an understanding of the most modern techniques and uses for data mining. It examines data mining in order to classify datasets, predict outcomes, and optimize analyses. Furthermore, the book demonstrates these technological developments by highlighting relevant applications of data mining in industry, biology, education, medicine, and health.
dc.languageEnglish
dc.relation.ispartofseriesArtificial Intelligence
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learning
dc.subject.otherMachine learning
dc.titleResearch Advances in Data Mining Techniques and Applications
dc.typebook
oapen.identifier.doi10.5772/intechopen.107722
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9781837690794
oapen.relation.isbn9781837690787
oapen.relation.isbn9781837690800
oapen.imprintIntechOpen
oapen.series.number25
oapen.pages160


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