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Data mining and exploration :from traditional statistics to modern data science /

紀錄類型:	書目-語言資料,印刷品 : 單行本
正題名/作者:	Data mining and exploration :/ Chong Ho Alex Yu.
其他題名:	from traditional statistics to modern data science /
作者:	Yu, Chong Ho,
出版者:	Boca Raton :CRC Press,c2022.
面頁冊數:	ix, 279 p. :ill. (some col.), maps (some col.) ;24 cm.
附註:	"A Science Publishers book."
標題:	Data mining. -
ISBN:	9780367721466
ISBN:	9780367721510
ISBN:	9781003153658

Data mining and exploration :from traditional statistics to modern data science /
Yu, Chong Ho,1963-

Data mining and exploration :from traditional statistics to modern data science /Chong Ho Alex Yu. - 1st ed. - Boca Raton :CRC Press,c2022. - ix, 279 p. :ill. (some col.), maps (some col.) ;24 cm.

"A Science Publishers book."

Includes bibliographical references and index.

"This book will introduce both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. Most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between these two schools of thought, and as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a "black box", without a comprehensive view of the foundational differences between traditional and modern methods (e.g. dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation...etc.). To remediate this problem, this book will provide the readers with the details of the similarities and differences between classical methods and data science, as well as the path for the transition (e.g. from p value to LogWorth, from resampling to ensemble methods, from content analysis to text mining...etc.)"--

ISBN: 9780367721466NT4033

LCCN: 2022009914Subjects--Topical Terms:

147024
Data mining.

LC Class. No.: QA76.9.D343 / Y837 2022

Dewey Class. No.: 006.3/12

Data mining and exploration :from traditional statistics to modern data science /
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245 1 0 $a Data mining and exploration : $b from traditional statistics to modern data science / $c Chong Ho Alex Yu.
250 $a 1st ed.
260 $a Boca Raton : $b CRC Press, $c c2022.
300 $a ix, 279 p. : $b ill. (some col.), maps (some col.) ; $c 24 cm.
500 $a "A Science Publishers book."
504 $a Includes bibliographical references and index.
520 $a "This book will introduce both conceptual and procedural aspects of cutting-edge data science methods, such as dynamic data visualization, artificial neural networks, ensemble methods, and text mining. There are at least two unique elements that can set the book apart from its rivals. Most students in social sciences, engineering, and business took at least one class in introductory statistics before learning data science. However, usually these courses do not discuss the similarities and differences between these two schools of thought, and as a result learners are disoriented by this seemingly drastic paradigm shift. In reaction, some traditionalists reject data science altogether while some beginning data analysts employ data mining tools as a "black box", without a comprehensive view of the foundational differences between traditional and modern methods (e.g. dichotomous thinking vs. pattern recognition, confirmation vs. exploration, single method vs. triangulation, single sample vs. cross-validation...etc.). To remediate this problem, this book will provide the readers with the details of the similarities and differences between classical methods and data science, as well as the path for the transition (e.g. from p value to LogWorth, from resampling to ensemble methods, from content analysis to text mining...etc.)"-- $c Provided by publisher.
650 0 $a Data mining. $3 147024