Supervised machine learning : optimization framework and applications with SAS and R /: optimization framework and applications with SAS and R. (2020)

• Record Type: Book
• Further Information: Note: Tanya Kolosova, Samuel Berestizhevsky.
• Authors: Kolosova, Tanya; Berestizhevsky, Samuel
• Contents: Introduction PART 1 Introduction to the AI framework Supervised Machine Learning and Its Deployment in SAS and R Bootstrap methods and Its Deployment in SAS and R Outliers Detection and Its Deployment in SAS and R Design of Experiment and Its Deployment in SAS and R PART II Introduction to the SAS and R based table-driven environment Input Data component Design of Experiment for Machine-Learning component "Contaminated" Training Datasets Component PART III Insurance Industry: Underwriters decision-making process Insurance Industry: Claims Modeling and Prediction Index
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2020
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 006.31; Machine learning; R (Computer program language); SAS (Computer program language)
• Languages: English
• ISBNs: 9781000176834; 9781000176810; 9780429297595
• Related ISBNs: 9780367277321
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.