摘要近年来，随着电子信息业的迅猛发展，人们已然进入了一个新的时代——大数据时代。而人工智能作为新时代发展的大方向，则将电子行业很快引入了快速发展的可能性，并渗透到我们生活里的方方面面，逐渐发展成为现代电子信息行业的重要支柱之一。人读懂机器的语言已经是完成时，在这个时代里，让机器“读懂”人的需求才是我们现在的任务。如何能够快速有效的利用人工智能来筛选有用数据并进行数据分析成了当今社会研讨的重中之重。本文所要使用的朴素贝叶斯算法是最为广泛应用的分类算法之一。以贝叶斯定理作为坚实的理论基础。贝叶斯分类是许多分类算法中的通用术语。也是数据挖掘领域十大经典算法之一。本文将从机器学习的概念入手，深入浅出的介绍机器学习的概念、应用现状和发展前景。对机器学习中的朴素贝叶斯模型的基本原理进行研究。通过对于人们是否购买化妆品预测的实例，并对一个人购买化妆品是否受到年龄、收入、是否为学生、信用等级这四个方面进行层层剖析。使用机器学习中的贝叶斯模型来进行预判和分类，通过 python 语言最终在案例上实现在购物意愿判断上的应用的想法。关键词：机器学习；贝叶斯定理；朴素贝叶斯模型 1 / 29ABSTRACTIn recent years, with the rapid development of the electronic information industry, people have entered a new era - the era of big data. As the general direction of the development of the new era, artificial intelligence has quickly introduced the possibility of rapid development, and penetrated into all aspects of our lives, and gradually developed into one of the important pillars of the modern electronic information industry. When people understand the language of the machine is complete, in this era, let the machine "read and understand" the needs of people is our current task. How to quickly and effectively use artificial intelligence to screen useful data and analyze data has become the top priority of today's society. The naive Bayesian algorithm used in this paper is one of the most widely used classification algorithms. Bayesian theorem is used as a solid...
