Handbook of Big Data Analytics

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Härdle, Wolfgang Karl (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Lu, Henry Horng-Shing (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Shen, Xiaotong (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Σειρά: Springer Handbooks of Computational Statistics,
• Θέματα: Statistics .; Data mining.; Applied mathematics.; Engineering mathematics.; Statistics and Computing/Statistics Programs.; Data Mining and Knowledge Discovery.; Mathematical and Computational Engineering.; Statistical Theory and Methods.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
• Φυσική περιγραφή: VIII, 538 p. 147 illus., 109 illus. in color. online resource.
• ISBN: 9783319182841
• ISSN: 2197-9790
• DOI: 10.1007/978-3-319-18284-1

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science. .