Then, in 1860 the French explorer Henri Mahout set out to find Angkor.

后来，在1860年，法国探险家亨利·马乌开始寻找吴哥。

The first essential in elephant training is to assign to the animal a single mahout who will be entirely responsible for the job.

驯象首要之事是给它指定一位驯象者,全面负责这项工作。

The first essential in elephant training is to assign to the animal a single mahout who will be entirely responsible for the job.

驯象中至关重要的是，为大象指派一个专门的、全面负责这项工作的驯象员。

Such extreme cases must probably be taken with a grain of salt, but they do underline the general principle that the relation-ship between elephant and mahout is the key to successful training.

这种极端事例或许不可全信,但确也说明了象和驯象者之间的关系是成功驯养的关键这一普遍原则。

"What’s the meaning of this? " he shouted to the mahout .

“这是什么意思呀？”他大声问了问那个看象人。

Mahout contains implementations for clustering, categorization, CF, and evolutionary programming.

Mahout包含许多实现，包括集群、分类、CP和进化程序。

However, for this article, I’ll show only the Naive Bayes approach, because it demonstrates the overall problem and inputs in Mahout .

但在本文中，我只会演示NaiveBayes方法，因为这能让您看到总体问题和Mahout中的输入。

Then I’ll show you how to use Mahout to do some interesting machine-learning tasks using the freely available Wikipedia data set.

然后，我将演示如何使用Mahout完成一些有趣的机器学习任务，这需要使用免费的Wikipedia数据集。

Run the clustering algorithm of choice using one of the many Hadoop-ready driver programs available in Mahout .

使用Mahout中可用的Hadoop就绪的驱动程序运行所选集群算法。

The next time you have a need to cluster, categorize, or recommend content, especially at large scale, give Apache Mahout a look.

下次在需要集群、分类或推荐内容时，特别是规模很大时，一定要考虑使用ApacheMahout。

Thus, to run Mahout ’s classifier, you need to first train the model and then use that model to classify new content.

因此，要运行Mahout的分类器，您首先需要训练模式，然后再使用该模式对新内容进行分类。

You’ll find more information on choosing a similarity measure at the Mahout Web site (see Resources).

有关如何选择相似度度量的更多信息，请访问Mahout网站（见参考资料）。

The results of running these two steps is a file like the n2. tar. gz file you downloaded in the Getting started with Mahout section.

运行这两个步骤的结果是生成一个文件，该文件类似于与您从GettingstartedwithMahout入门部分下载的n2.tar.gz文件。

After giving a brief overview of machine-learning concepts, I’ll introduce you to the Apache Mahout project’s features, history, and goals.

在简要概述机器学习的概念之后，我将介绍ApacheMahout项目的特性、历史和目标。

In your use of Mahout , you will likely want to try creating vectors in a variety of ways to see which yields the best results.

在使用Mahout时，您可能希望尝试采用不同的方法来创建矢量，以确定哪种方法的效果最好。

I’ll take a deeper look at each of these tasks at the conceptual level before exploring their implementations in Mahout .

在研究它们在Mahout中的实现之前，我将从概念的层面上更加深入地讨论这些任务。

The output from such a test in Mahout is a data structure called a confusion matrix.

这种测试在Mahout中输出的数据结构是混合矩阵。