Titlebook: Big Data Analytics; Methods and Applicat Saumyadipta Pyne,B.L.S. Prakasa Rao,S.B. Rao Book 2016 Springer India 2016 Big Data.Computational

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書目名稱Big Data Analytics影響因子(影響力)




書目名稱Big Data Analytics影響因子(影響力)學(xué)科排名




書目名稱Big Data Analytics網(wǎng)絡(luò)公開度




書目名稱Big Data Analytics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Big Data Analytics被引頻次




書目名稱Big Data Analytics被引頻次學(xué)科排名




書目名稱Big Data Analytics年度引用




書目名稱Big Data Analytics年度引用學(xué)科排名




書目名稱Big Data Analytics讀者反饋




書目名稱Big Data Analytics讀者反饋學(xué)科排名

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aesthetician

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Application of Mixture Models to Large Datasets,sider normal and .-mixture models. As they are highly parameterized, we review methods to enable them to be fitted to large datasets involving many observations and variables. Attention is then given to extensions of these mixture models to mixtures with skew normal and skew .-distributions for the

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Spinal-Fusion

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Systemic

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Application-Level Benchmarking of Big Data Systems, phenomenon. The amount, rate, and variety of data that are assembled—for almost any application domain—are necessitating a reexamination of old technologies and development of new technologies to get value from the data, in a timely fashion. With increasing adoption and penetration of mobile techno