“They didn’t pay me, ” the mahout said.
他们没有付钱给我呢。
“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。
Early one morning, Ladyface's mahout came to see him as usual.
一天清晨，“菩萨相”的看象人如常来看他。
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。
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。
To do so, you need the Mahout Job JAR, which is located in the hadoop directory in the sample code.
为此，您需要Mahout JobJAR，它位于示例代码的hadoop目录中。
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）。
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 mahout turned and gesticulated at him with his iron rod. A passerby yelled at him not to block traffic.
身后响起了汽车喇叭声，看象人也用小铁棒向他比划着，一个过路人更对他吼着让他不要妨碍交通。
If he charged, I could shoot; if he took no notice of me, it would be safe to leave him until the mahout came back.
它要是向我冲过来，那我就开枪；它要是不理我，那就不会再有危险，就由它去，等驯象人回来再说。
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。
Another important aspect of the Mahout solution is the set of tools for creating vector representations of textual data.
Mahout另一个重点是，它提供一系列工 具把文本数据表示成矩阵形式。
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。
Gripping my hair with both hands, his own long hair blowing in the wind, he rode me like a mahout rides a baggy old elephant.
他用手抓住我的头发，他的长头发在风中飞舞，他骑在我身上，就像一名驯象师骑着一匹又肥又老的大象。
Mahout currently provides tools for building a recommendation engine through the Taste library - a fast and flexible engine for CF.
Mahout目前提供了一些工具，可用于通过taste库建立一个推荐引擎—针对CF的快速且灵活的引擎。
Mahout provides driver programs for all of the clustering algorithms, including the k-Means algorithm, aptly named the KMeansDriver.
Mahout为所有集群算法都提供了驱动程序，包括k - Means算法，更合适的名称应该是KMeansDriver。
Mahout supports several clustering-algorithm implementations, all written in Map-Reduce, each with its own set of goals and criteria.
Mahout支持一些集群算法实现(都是使用Map - Reduce编写的)，它们都有一组各自的目标和标准。
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Naive Bayes方法，因为这能让您看到总体问题和Mahout中的输入。
The first essential in elephant training is to assign to the animal a single mahout who will be entirely responsible for the job.
驯象中至关生要的是指派一名专门的驯象员，全面负责这项工作。
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。
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。
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Gettingstarted with Mahout入门部分下载的n2 . tar . gz文件。
Cars honked behind him. The mahout turned and gesticulated at him with his iron rod. A passerby yelled at him not to block traffic.
身后响起了汽车喇叭声，看象人也用小铁棒向他比划着，一个过路人更对他吼着让他不要妨碍交通。
I'll focus on the two most commonly used ones - supervised and unsupervised learning - because they are the main ones supported by Mahout.
我将重点讨论其中最常用的两个—监管和无监管学习—因为它们是Mahout支持的主要功能。
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。
Halfway up the hill, he saw an elephant coming down, with a small bundle of leaves on its back and a mahout poking its ear with an iron rod.
就在上到半山腰的时候，他看到了迎面走过来一头大象，大象背上背着一小捆树叶，旁边看象人拿一根小铁棒在拨弄着它的耳朵。
Therein lies the premise and the promise of the field of machine learning and the project this article introduces: Apache Mahout (see Resources).
这其中就蕴含着机器学习领域以及本文章所介绍项目的前景：ApacheMahout（见参考资料）。
The final results are stored in a single file labeled with the category name, one document per line, which is the input format that Mahout expects.
最终结果将存储在一个特定的文件中（该文件名包含类别名），并采用每行一个文档的格式，这是 Mahout 所需的输入格式。
The final results are stored in a single file labeled with the category name, one document per line, which is the input format that Mahout expects.
最终结果将存储在一个特定的文件中（该文件名包含类别名），并采用每行一个文档的格式，这是 Mahout 所需的输入格式。
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