Supervised machine learning : optimization framework and applications with SAS and R /

Bibliographic Details
Main Authors:	Kolosova, Tanya (Author), Berestizhevsky, Samuel (Author)
Corporate Author:	EBSCOhost
Format:	eBook
Language:	English
Published:	Boca Raton, FL : CRC Press, 2021.
Edition:	First edition.
Subjects:	Supervised learning (Machine learning) Program transformation (Computer programming) SAS (Computer program language) R (Computer program language) Apprentissage supervisé (Intelligence artificielle) Transformation de programme (Informatique) SAS (Langage de programmation) R (Langage de programmation) COMPUTERS > Machine Theory. COMPUTERS > Mathematical & Statistical Software. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

IntroductionPART 1Introduction to the AI frameworkSupervised Machine Learning and Its Deployment in SAS and RBootstrap methods and Its Deployment in SAS and ROutliers Detection and Its Deployment in SAS and RDesign of Experiment and Its Deployment in SAS and RPART IIIntroduction to the SAS and R based table-driven environmentInput Data componentDesign of Experiment for Machine-Learning component"Contaminated" Training Datasets ComponentPART IIIInsurance Industry: Underwriters decision-making processInsurance Industry: Claims Modeling and PredictionIndex