Forecasting Methods For Horseracing

Description

Computer-based forecasting methods are no longer restricted to the traditional statistical methods. Knowledge-based approaches, which utilise the knowledge gained from human experts in their construction, and machine learning methods, in which the computer learns from available examples without significant human intervention, are now in general use as forecasting tools. In this book, May examines the application of these methods to the domain of horseracing in Great Britain and overseas and provides a detailed step-by-step guide to implementing these methods.

Peter May has a Master Of Philosophy degree in expert systems and a PhD in artificial intelligence at Oxford Brookes University. He has written six books, including Flat Racing For Profit and Jump Racing For Profit and covered the National Hunt Ratings, Juvenile Ratings and Trainer Form columns for the national racing newspaper Raceform On Saturday and he still writes regular columns for Raceform Update. He lives near Oxford and is available for interview.