國立虎尾科技大學 |

Handbook of Big Data Analytics

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Handbook of Big Data Analytics/ edited by Wolfgang Karl Härdle, Henry Horng-Shing Lu, Xiaotong Shen.
其他作者:	Härdle, Wolfgang Karl.
面頁冊數:	VIII, 538 p. 147 illus., 109 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Statistics . -
電子資源:	https://doi.org/10.1007/978-3-319-18284-1
ISBN:	9783319182841

Handbook of Big Data Analytics
Handbook of Big Data Analytics[electronic resource] /edited by Wolfgang Karl Härdle, Henry Horng-Shing Lu, Xiaotong Shen. - 1st ed. 2018. - VIII, 538 p. 147 illus., 109 illus. in color.online resource. - Springer Handbooks of Computational Statistics,2197-9790. - Springer Handbooks of Computational Statistics,.

Preface -- Statistics, Statisticians, and the Internet of Things (John M. Jordan and Dennis K. J. Lin) -- Cognitive Data Analysis for Big Data (Jing Shyr, Jane Chu and Mike Woods) -- Statistical Leveraging Methods in Big Data (Xinlian Zhang, Rui Xie and Ping Ma) -- Scattered Data and Aggregated Inference (Xiaoming Huo, Cheng Huang and Xuelei Sherry Ni) -- Nonparametric Methods for Big Data Analytics (Hao Helen Zhang) -- Finding Patterns in Time Series (James E. Gentle and Seunghye J. Wilson) -- Variational Bayes for Hierarchical Mixture Models (Muting Wan, James G. Booth and Martin T. Wells) -- Hypothesis Testing for High-Dimensional Data (Wei Biao Wu, Zhipeng Lou and Yuefeng Han) -- High-Dimensional Classification (Hui Zou) -- Analysis of High-Dimensional Regression Models Using Orthogonal Greedy Algorithms (Hsiang-Ling Hsu, Ching-Kang Ing and Tze Leung Lai) -- Semi-Supervised Smoothing for Large Data Problems (Mark Vere Culp, Kenneth Joseph Ryan and George Michailidis) -- Inverse Modeling: A Strategy to Cope with Non-Linearity (Qian Lin, Yang Li and Jun S. Liu) -- Sufficient Dimension Reduction for Tensor Data (Yiwen Liu, Xin Xing and Wenxuan Zhong) -- Compressive Sensing and Sparse Coding (Kevin Chen and H. T. Kung) -- Bridging Density Functional Theory and Big Data Analytics with Applications (Chien-Chang Chen, Hung-Hui Juan, Meng-Yuan Tsai and Henry Horng-Shing Lu) -- Q3-D3-LSA: D3.js and generalized vector space models for Statistical Computing (Lukas Borke and Wolfgang Karl Härdle) -- A Tutorial on Libra: R Package for the Linearized Bregman Algorithm in High-Dimensional Statistics (Jiechao Xiong, Feng Ruan and Yuan Yao) -- Functional Data Analysis for Big Data: A Case Study on California Temperature Trends (Pantelis Zenon Hadjipantelis and Hans-Georg Müller) -- Bayesian Spatiotemporal Modeling for Detecting Neuronal Activation via Functional Magnetic Resonance Imaging (Martin Bezener, Lynn E. Eberly, John Hughes, Galin Jones and Donald R. Musgrove) -- Construction of Tight Frames on Graphs and Application to Denoising (Franziska Göbel, Gilles Blanchard and Ulrike von Luxburg) -- Beta-Boosted Ensemble for Big Credit Scoring Data (Maciej Zięba and Wolfgang Karl Härdle) -- .

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. .

ISBN: 9783319182841

Standard No.: 10.1007/978-3-319-18284-1doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Handbook of Big Data Analytics
LDR:04345nam a22004095i 4500 001 990517
003 DE-He213
005 20200702070938.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319182841 $9 978-3-319-18284-1
024 7 $a 10.1007/978-3-319-18284-1 $2 doi
035 $a 978-3-319-18284-1
050 4 $a QA276-280
072 7 $a UFM $2 bicssc
072 7 $a COM077000 $2 bisacsh
072 7 $a UFM $2 thema
082 0 4 $a 519.5 $2 23
245 1 0 $a Handbook of Big Data Analytics $h [electronic resource] / $c edited by Wolfgang Karl Härdle, Henry Horng-Shing Lu, Xiaotong Shen.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a VIII, 538 p. 147 illus., 109 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Handbooks of Computational Statistics, $x 2197-9790
505 0 $a Preface -- Statistics, Statisticians, and the Internet of Things (John M. Jordan and Dennis K. J. Lin) -- Cognitive Data Analysis for Big Data (Jing Shyr, Jane Chu and Mike Woods) -- Statistical Leveraging Methods in Big Data (Xinlian Zhang, Rui Xie and Ping Ma) -- Scattered Data and Aggregated Inference (Xiaoming Huo, Cheng Huang and Xuelei Sherry Ni) -- Nonparametric Methods for Big Data Analytics (Hao Helen Zhang) -- Finding Patterns in Time Series (James E. Gentle and Seunghye J. Wilson) -- Variational Bayes for Hierarchical Mixture Models (Muting Wan, James G. Booth and Martin T. Wells) -- Hypothesis Testing for High-Dimensional Data (Wei Biao Wu, Zhipeng Lou and Yuefeng Han) -- High-Dimensional Classification (Hui Zou) -- Analysis of High-Dimensional Regression Models Using Orthogonal Greedy Algorithms (Hsiang-Ling Hsu, Ching-Kang Ing and Tze Leung Lai) -- Semi-Supervised Smoothing for Large Data Problems (Mark Vere Culp, Kenneth Joseph Ryan and George Michailidis) -- Inverse Modeling: A Strategy to Cope with Non-Linearity (Qian Lin, Yang Li and Jun S. Liu) -- Sufficient Dimension Reduction for Tensor Data (Yiwen Liu, Xin Xing and Wenxuan Zhong) -- Compressive Sensing and Sparse Coding (Kevin Chen and H. T. Kung) -- Bridging Density Functional Theory and Big Data Analytics with Applications (Chien-Chang Chen, Hung-Hui Juan, Meng-Yuan Tsai and Henry Horng-Shing Lu) -- Q3-D3-LSA: D3.js and generalized vector space models for Statistical Computing (Lukas Borke and Wolfgang Karl Härdle) -- A Tutorial on Libra: R Package for the Linearized Bregman Algorithm in High-Dimensional Statistics (Jiechao Xiong, Feng Ruan and Yuan Yao) -- Functional Data Analysis for Big Data: A Case Study on California Temperature Trends (Pantelis Zenon Hadjipantelis and Hans-Georg Müller) -- Bayesian Spatiotemporal Modeling for Detecting Neuronal Activation via Functional Magnetic Resonance Imaging (Martin Bezener, Lynn E. Eberly, John Hughes, Galin Jones and Donald R. Musgrove) -- Construction of Tight Frames on Graphs and Application to Denoising (Franziska Göbel, Gilles Blanchard and Ulrike von Luxburg) -- Beta-Boosted Ensemble for Big Credit Scoring Data (Maciej Zięba and Wolfgang Karl Härdle) -- .
520 $a 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. .
650 0 $a Statistics . $3 1253516
650 0 $a Data mining. $3 528622
650 0 $a Applied mathematics. $3 1069907
650 0 $a Engineering mathematics. $3 562757
650 1 4 $a Statistics and Computing/Statistics Programs. $3 669775
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Mathematical and Computational Engineering. $3 1139415
650 2 4 $a Statistical Theory and Methods. $3 671396
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 782247
700 1 $a Härdle, Wolfgang Karl. $e author. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1257587
700 1 $a Lu, Henry Horng-Shing. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 788103
700 1 $a Shen, Xiaotong. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1207635
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319182834
776 0 8 $i Printed edition: $z 9783319182858
776 0 8 $i Printed edition: $z 9783030132385
830 0 $a Springer Handbooks of Computational Statistics, $x 2197-9790 $3 1282210
856 4 0 $u https://doi.org/10.1007/978-3-319-18284-1
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)