The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables

• Main Authors: Zahari, Taha, Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah, Muhammad Amirul, Abdullah, M. H. A., Hassan, Zubair, Khalil
• Format: Conference or Workshop Item
• Language: English
• Published: IOP Publishing 2018
• Subjects: TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/21233/1/employment%20of%20Support%20Vector%20Machine%20to%20classify%20high-fkp-2018.pdf; http://umpir.ump.edu.my/id/eprint/21233/; https://doi.org/10.1088/1757-899X/342/1/012020
• Institution: Universiti Malaysia Pahang

The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from...