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Predictive Analytics: Parametric Models for Regression and Classification Using R

Contributor(s): Tamhane, Ajit C (Author)

ISBN: 9781118948897

Publisher: Wiley

Hardcover
$115.50
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Pub Date: October 13, 2020

Dewey: 006.312

LCCN: 2020034678

Lexile Code: 0000

Features: Index

Target Age Group: NA to NA

Physical Info: 1.00" H x 10.10" L x 7.20" W ( 1.90 lbs) 384 pages

Series: Wiley Probability and Statistics

Descriptions, Reviews, etc.

Description: "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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