我也是刚刚开始学习Weka，第一课先来翻译一下该项目的首页，水平有限，呵呵。如果您想阅读原文请直接到Weka Machine Learning Project。

在计算机科学领域，一项令人激动的和具有潜在深远影响的开发活动是机器学习方法的发明和应用。这些使得计算机程序能够自动分析大的数据集，决定什么信息是最有意义的。然后这些信息可以用来自动进行预测，或帮助用户更加快速和准确的做出决策。

我们整体的目标是为开发机器学习技术和解决真实世界中数据挖掘问题提供便利。我们的团队已经合并了一些机器学习技术到"workbench"软件包中，这个包被称为WEKA。使用它，一些特殊的领域能够使用机器学习来从手工无法处理的大量数据中推导有用的知识。Weka的用户是机器学习领域的研究者和工业界的科学家，但是Weka也被广泛的用于教学。

我们的目标是：

• 使机器学习(ML)成为普遍可用的技术
• 使用这些技术解决新西兰工业中重要的实际问题
• 开发新的机器学习算法并将它们推广到全世界
• 为机器学习领域贡献一个理论框架

我们的机器学习包是公开可用的，包含有一个解决真实世界中数据挖掘问题的算法集合。这个软件包全部用Java写成并且包含一个标准机器学习技术的统一接口。请到处随便浏览一下。

[翻译完]

最后给出Weka的论坛和邮件类表，有兴趣的朋友可以去看看。

Weka 3: Data Mining Software in Java

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.

Weka is open source software issued under the GNU General Public License.

Pentaho's live forum for Weka

The open-source BI software company Pentaho has become major sponsor of Weka development and will take over the administration of Weka's Sourceforge site in the near future. Pentaho also provides a live forum for interaction among Weka project community members.

The Weka mailing list

Please post Weka-related questions, comments, and bug reports to the Weka mailing list (don't forget to check out the online documentation first, before posting to the list). There is also the searchable mailing list archive (Mirrors: news.gmane.org, Nabble). Please do not email individual members of our research group about Weka problems.

Also, please have in mind that your message will be sent to several thousand people, so please post according to the Mailing List Etiquette. The administrator also removes members from the mailing list in case their mailboxes run full, since they apparently don't read their emails anymore.