Kolosova,Tanya <br/><br/>
Supervised Machine Learning :  Optimization Framework and Applications with SAS and R/ 
Tanya Kolosova, Samuel Berestizhevsky 
 - 1st ed. 
 - New York :  CRC Press ,  2021. 
 - xx, 160 p. :   ill.  ;  23 cm. 
<br/><br/>Includes bibliographical references and index. 
<br/><br/> Introduction. PART 1 1.Introduction to the AI framework.   2.Supervised Machine Learning and Its Deployment in SAS and R.   3.Bootstrap methods and Its Deployment in SAS and R.   4.Outliers Detection and Its Deployment in SAS and R.   5.Design of Experiment and Its Deployment in SAS and R.   PART II 1.Introduction to the SAS and R based table-driven environment.   2.Input Data component.   3.Design of Experiment for Machine-Learning component.   4.“Contaminated” Training Datasets Component.   PART III 1.Insurance Industry: Underwriters decision-making process.   2.Insurance Industry: Claims Modeling and Prediction.  
<br/><br/><label>ISBN: </label>9780367538828 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Machine learning <br/>R (Computer program language) <br/>SAS (Computer program language)
<br/><br/><label>Dewey Class. No.: </label>006.31  / KOS