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Predictive analytics :parametric models for regression and classification using R /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Predictive analytics :Ajit C. Tamhane ; with contributions from Edward C. Malthouse.
其他題名:	parametric models for regression and classification using R /
作者:	Tamhane, Ajit C.,
其他作者:	Malthouse, Edward C.,
出版者:	Hoboken, NJ :John Wiley & Sons, Inc.,2021.
面頁冊數:	xxi, 359 p. :ill. ;26 cm.
標題:	Data miningStatistical methods.
ISBN:	9781118948897 :

Predictive analytics :parametric models for regression and classification using R /
Tamhane, Ajit C.,

Predictive analytics :parametric models for regression and classification using R /Ajit C. Tamhane ; with contributions from Edward C. Malthouse. - Hoboken, NJ :John Wiley & Sons, Inc.,2021. - xxi, 359 p. :ill. ;26 cm. - Wiley series in probability and statistics. - Wiley series in probability and statistics..

Includes bibliographical references (p. 339-341) and index.

"Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior. For example, an insurance company is likely to take into account potential driving safety predictors such as age, gender, and driving record when issuing car insurance policies. Multiple predictors are combined into a predictive model, which, when subjected to analysis, can be used to forecast future probabilities with an acceptable level of reliability. In predictive modeling, data is collected, a statistical model is formulated, predictions are made and the model is validated (or revised) as additional data becomes available. Predictive analytics are applied to many research areas, including meteorology, security, genetics, economics, and marketing, among others. The use of a computer can alleviate stressful computations, especially those involving big data"--

ISBN: 9781118948897 :NT$4087

LCCN: 2020034678Subjects--Topical Terms:

289696
Data mining
--Statistical methods.

LC Class. No.: QA76.9.D343 / T349 2021

Dewey Class. No.: 006.3/12

Predictive analytics :parametric models for regression and classification using R /
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245 1 0 $a Predictive analytics : $b parametric models for regression and classification using R / $c Ajit C. Tamhane ; with contributions from Edward C. Malthouse.
260 $a Hoboken, NJ : $b John Wiley & Sons, Inc., $c 2021.
300 $a xxi, 359 p. : $b ill. ; $c 26 cm.
490 1 $a Wiley series in probability and statistics
504 $a Includes bibliographical references (p. 339-341) and index.
520 $a "Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior. For example, an insurance company is likely to take into account potential driving safety predictors such as age, gender, and driving record when issuing car insurance policies. Multiple predictors are combined into a predictive model, which, when subjected to analysis, can be used to forecast future probabilities with an acceptable level of reliability. In predictive modeling, data is collected, a statistical model is formulated, predictions are made and the model is validated (or revised) as additional data becomes available. Predictive analytics are applied to many research areas, including meteorology, security, genetics, economics, and marketing, among others. The use of a computer can alleviate stressful computations, especially those involving big data"-- $c Provided by publisher.
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650 0 $a Probabilities. $3 182046
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