机器学习在数据分析中的实践与应用

Practice of machine learning in data analysis

机器学习技术能够使机器从大量的数据中学习规律,从而对新的样本做出分类识别,或者对未来做出合理的预测。本文应用鸢尾花数据集介绍了机器学习应用于数据分析的一般流程,分析与比较了典型的机器学习数据分析方法,比如主成分分析、线性判别分析和K-Means聚类等方法,阐述了机器学习在数据分析中的实践与应用。

Machine learning enables machines to learn rules from large amounts of data,so as to classify new samples or make reasonable predictions about the future.This paper introduces the general process of machine learning applied to data analysis by using iris plants database,analyzes and compares typical machine learning methods in data analysis,such as principal component analysis,linear discriminant analysis and K-means clustering,and expounds the practice of m achine learning in data analysis.