This book is a practical guide that explains the classification algorithms provided in Apache Mahout with the help of actual examples. Starting with the introduction of classification and model evaluation techniques, we will explore Apache Mahout and learn why it is a good choice for classification. Next, you will learn about different classification algorithms and models such as the Naïve Bayes algorithm, the Hidden Markov Model, and so on. Finally, along with the examples that assist you in the creation of models, this book helps you to build a mail classification system that can be produced as soon as it is developed. After reading this book, you will be able to understand the concept of classification and the various algorithms along with the art of building your own classifiers.

本书是一本实用指南，通过实际例子解释Apache Mahout中提供的分类算法。从介绍分类和模型评估技术开始，我们将探索Apache Mahout，了解为什么它是分类的好选择。接下来，你将了解不同的分类算法和模型，如Naïve Bayes算法、隐马尔科夫模型等等。最后，伴随着协助你创建模型的例子，本书帮助你建立一个邮件分类系统，该系统一经开发就可以投入生产。读完本书后，你将能够理解分类的概念和各种算法，同时掌握建立自己的分类器的艺术。