Machine Learning Mining of Athlete Event Data

现在人们普遍认识到，使用机器学习技术可以从数据集中提取以前未知的知识。特别地，规则归纳算法以直接服从人类理解的形式捕获数据的结构。该项目将探索一种规则归纳形式的实用性，这种规则归纳形式将进化计算与强化学习相结合，以产生人类可读的解决方案，从而促进英国游泳队种族分析方面的知识发现。该技术，被称为学习分类系统（LCS），最近显示出巨大的潜力，数据挖掘问题。LCS与其他机器学习方法沿着将用于探索英国游泳队合作教练提供的运动员数据集。

There is now widespread recognition that it is possible to extract previously unknown knowledge from datasets using machine learning techniques. In particular, rule induction algorithms capture the structure of data in a form directly amenable to human understanding. This project will explore the utility of a form of rule induction which combines evolutionary computation with reinforcement learning to produce human-readable solutions to facilitate knowledge discovery with respect to race analyses of the British swimming team. The technique, known as the Learning Classifier System (LCS), has recently shown great potential for data mining problems. LCS, along with other machine learning approaches, will be used to explore athlete datasets provided by the collaborating coach of the British swimming team.