E4ML: Educational Tool for Machine Learning

• Main Authors: Sainin, Mohd Shamrie, Siraj, Fadzilah
• Format: Conference or Workshop Item
• Language: English
• Published: 2003
• Subjects: QA Mathematics
• Online Access: http://repo.uum.edu.my/12531/1/e4ML.pdf; http://repo.uum.edu.my/12531/

There are various types of machine learning algorithms with certain processes taken by the algorithm.In teaching of the machine learning algorithms, such processes need to be explained especially to the beginner in introductory level.This paper discusses the development the tool that addresses the process by certain algorithm to produce a hypothesis or output based on given data.This tool can also be used in teaching and learning purposes.The explanation of processes by the algorithms is demonstrated through simple simulation.The source of the algorithms was adapted from Mitchell book [1] that cover popular algorithms in machine learning for teaching and learning such as Concept Learning, Decision Tree, Bayesian Learning, Neural Networks, and Instance based Learning.The tool also used several classes of Weka (Waikato Environment for Knowledge Analysis) as a basis for the design and implementation of the new tool that focuses on explaining the processes taken by certain algorithm.