Photo by Mathew Schwartz on Unsplash
Photo by Mathew Schwartz on Unsplash
For this project, I’m using Hong Kong horse racing data from Kaggle.com (https://www.kaggle.com/gdaley/hkracing) to predict which kinds of horses win races. Factors to be considered are the horse’s age, weight, type, and country of origin. The type variable is comprised of the sex and age-related categories of a horse, specifically 'Gelding', 'Mare', 'Horse', 'Rig', 'Colt', and 'Filly' (Daley, 2019). In terms of specific methods, I use graph analysis, dimensionality and feature reduction, model evaluation and selection to predict which horses will win.
Horse racing is a giant industry in Hong Kong, with “betting pools bigger than all US racetracks combined” (Daley, 2019). Predicting wins could potentially lead to major financial gain for those interested in placing bets. Although I don’t necessarily condone horse racing, by analyzing the data I can hopefully bring more awareness to the subject and encourage discussions about it.
Daley, G. (2019, November 17). Horse Racing in HK. Kaggle. Retrieved from https://www.kaggle.com/gdaley/hkracing
Keith Prowse. (2018, May 16). Off to the races: A horse racing glossary. Retrieved from https://www.keithprowse.co.uk/news-and-blog/2018/05/16/off-to-the-races---a-horse-racing-glossary/
The content of this project itself is licensed under the Creative Commons Attribution 3.0 Unported license, and the underlying source code used to format and display that content is licensed under the MIT license.