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dc.contributor.editorPetrucci, Alessandra
dc.contributor.editorVERDE, Rosanna
dc.date.accessioned2022-06-02T04:30:30Z
dc.date.available2022-06-02T04:30:30Z
dc.date.issued2017
dc.date.submitted2022-05-31T10:28:45Z
dc.identifierONIX_20220531_9788864535210_690
dc.identifier2704-5846
dc.identifierhttps://library.oapen.org/handle/20.500.12657/55406
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/83410
dc.description.abstractThe 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data.
dc.languageItalian
dc.relation.ispartofseriesProceedings e report
dc.rightsopen access
dc.subject.classificationbic Book Industry Communication::J Society & social sciences::JH Sociology & anthropology::JHB Sociology
dc.titleSIS 2017. Statistics and Data Science: new challenges, new generations
dc.title.alternativeProceedings of the Conference of the Italian Statistical Society, Florence 28-30 June 2017
dc.typebook
oapen.identifier.doi10.36253/978-88-6453-521-0
oapen.relation.isPublishedBy2ec4474d-93b1-4cfa-b313-9c6019b51b1a
oapen.relation.isbn9788864535210
oapen.relation.isbn9788892731851
oapen.pages1066
oapen.place.publicationFlorence
dc.seriesnumber114
dc.abstractotherlanguageThe 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured. The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data.


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