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Predictive analytics : parametric models for regression and classification using R / Ajit C. Tamhane, Northwestern University ; with contributions from Edward C. Malthouse, Northwestern University

Author
Tamhane, Ajit C.
Published
Hoboken, NJ : Wiley, 2020.
Physical Description
1 online resource
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Summary
"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"--
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ISBN
9781119464761 (electronic bk. : oBook)
1119464765 (electronic bk. : oBook)
9781118948903 (epub)
1118948904 (epub)
9781118948910 (adobe pdf)
1118948912 (adobe pdf)
9781118948897 (cloth)
Note
Includes index.
View MARC record | catkey: 33843537