blocks|key|2646291|text|我相信WEKA是最好的开源DM软件。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2646292|检查它：http://www.cs.waikato.ac.nz/ml/weka/|offset|length|2646293|entityMap|0|LINK|mutability|MUTABLE|url|http://www.cs.waikato.ac.nz/ml/weka/^0|0|4|10|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

I believe WEKA is the best open source DM software out there.

Check it: <a href="http://www.cs.waikato.ac.nz/ml/weka/" rel="noreferrer">http://www.cs.waikato.ac.nz/ml/weka/</a>

blocks|key|2646339|text|Weka很棒，但是您可能想尝试一下Orange+Data+Mining工具包。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2646340|http://www.ailab.si/orange/|offset|length|2646341|编辑：，从2010年11月开始，我必须说我真的很喜欢KNIME。|style|BOLD|2646342|entityMap|0|LINK|mutability|MUTABLE|url|1|http://knime.org/^0|0|0|R|0|0|0|3|Q|5|1|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@$D|U|E|V|1|W]]|A|$]]|$1|F|3|G|5|6|7|X|8|@$D|Y|E|Z|H|I]]|9|@$D|10|E|11|1|12]]|A|$]]|$1|J|3|-4|5|6|7|13|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|C]]|Q|$5|M|N|O|A|$P|R]]]]

Weka is great, but you might want to try the Orange Data Mining toolkit instead.

<a href="http://www.ailab.si/orange/" rel="noreferrer">http://www.ailab.si/orange/</a>

Edit: And as of November 2010, I must say I really like <a href="http://knime.org" rel="noreferrer">KNIME</a>.

blocks|key|4759873|text|R有很多与数据挖掘相关的优秀包。特别要注意的是：|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4759874|4759875|The+machine+learning+view+on+CRAN.|unordered-list-item|4759876|The+natural+language+processing+view+on+CRAN.|4759877|4759878|它还与Weka+(see+the+RWeka+package)捆绑在一起。它可以与.Net+(通过COM)或Python+(通过RPy或RPy2)集成。|4759879|我同意将Pentaho作为一个报告平台，尽管这是一个非常大的项目，这取决于你使用它的目的。|4759880|entityMap|0|LINK|mutability|MUTABLE|url|http://www.r-project.org/|1|http://cran.r-project.org/web/views/MachineLearning.html|2|http://cran.r-project.org/web/views/NaturalLanguageProcessing.html|3|http://cran.r-project.org/web/packages/RWeka/index.html^0|0|1|0|0|0|0|Y|1|0|0|19|2|0|0|9|L|3|0|0^^$0|@$1|2|3|4|5|6|7|12|8|@]|9|@$A|13|B|14|1|15]]|C|$]]|$1|D|3|-4|5|6|7|16|8|@]|9|@]|C|$]]|$1|E|3|F|5|G|7|17|8|@]|9|@$A|18|B|19|1|1A]]|C|$]]|$1|H|3|I|5|G|7|1B|8|@]|9|@$A|1C|B|1D|1|1E]]|C|$]]|$1|J|3|-4|5|6|7|1F|8|@]|9|@]|C|$]]|$1|K|3|L|5|6|7|1G|8|@]|9|@$A|1H|B|1I|1|1J]]|C|$]]|$1|M|3|N|5|6|7|1K|8|@]|9|@]|C|$]]|$1|O|3|-4|5|6|7|1L|8|@]|9|@]|C|$]]]|P|$Q|$5|R|S|T|C|$U|V]]|W|$5|R|S|T|C|$U|X]]|Y|$5|R|S|T|C|$U|Z]]|10|$5|R|S|T|C|$U|11]]]]

<a href="http://www.r-project.org/" rel="nofollow noreferrer">R</a> has a lot of excellent packages related to data mining. In particular, look at:

<ul>
<li><a href="http://cran.r-project.org/web/views/MachineLearning.html" rel="nofollow noreferrer">The machine learning view on CRAN.</a></li>
<li><a href="http://cran.r-project.org/web/views/NaturalLanguageProcessing.html" rel="nofollow noreferrer">The natural language processing view on CRAN.</a></li>
</ul>

It also ties into Weka (<a href="http://cran.r-project.org/web/packages/RWeka/index.html" rel="nofollow noreferrer">see the RWeka package</a>). And it can be integrated with either .Net (through COM) or Python (through RPy or RPy2). 

I would agree regarding Pentaho for a reporting platform, although it's a very large project depending upon what you're using it for.

blocks|key|4759945|text|你也应该看看Apache+Mahout。它对于一些大规模的机器学习任务非常有用，比如用户聚类。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4759946|entityMap|0|LINK|mutability|MUTABLE|url|http://lucene.apache.org/mahout/^0|6|D|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

You should also check out <a href="http://lucene.apache.org/mahout/" rel="noreferrer">Apache Mahout</a> . It can be quite useful for some large-scale machine learning tasks such as user clustering.

blocks|key|1944808|text|是我首选的数据挖掘工具。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1944809|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

<a href="http://www.RapidMiner.com/" rel="noreferrer">RapidMiner</a> is my preferred data mining tool.

blocks|key|1939038|text|我会尝试使用新的google工具。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1939039|-first您需要获取google-storage的api，这是您将要存储和操作将要分析的数据的位置。|1939040|你需要获取google-+-Then+-+api+(http://code.google.com/apis/predict/docs/getting-started.html)的api+id，在我看来，它是一个很棒的外包数据挖掘处理器。预测API允许您从数据中获得更多信息，并使其模式更易于访问。除了使用传统的数字和名义数据外，您还可以使用文本数据，这要归功于此api，这些数据可以用于示例，以便按语言对电子邮件进行分类。|offset|length|1939041|-Finally您可以使用bigQuery执行即席分析、标准化报告、数据探索应用程序原型(http://code.google.com/apis/bigquery/)|1939042|entityMap|0|LINK|mutability|MUTABLE|url|http://code.google.com/apis/predict/docs/getting-started.html|1|http://code.google.com/apis/bigquery/^0|0|0|Q|1P|0|0|19|11|1|0^^$0|@$1|2|3|4|5|6|7|T|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|U|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|V|8|@]|9|@$F|W|G|X|1|Y]]|A|$]]|$1|H|3|I|5|6|7|Z|8|@]|9|@$F|10|G|11|1|12]]|A|$]]|$1|J|3|-4|5|6|7|13|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|Q]]|R|$5|M|N|O|A|$P|S]]]]

I would try with the new google tools.

-first you need to get the api id for the google-storage, which is where you are going to store and manipulate the data you are going to analyze. 

-Then you need to get the api id for google-prediction-api (http://code.google.com/apis/predict/docs/getting-started.html), which for what I saw it is a fantastic outsourced data mining processor. The Prediction API allows you to get more from your data and makes its patterns more accessible. Besides using traditional numeric and nominal data you can also use text data that thanks to this api can be utilized for exampled to categorize emails by language. 

-Finally you can use bigQuery that will allow you to perform Ad-hoc analysis, Standardized reporting, Data exploration App prototyping (http://code.google.com/apis/bigquery/)

blocks|key|1944849|text|KEEL+(http://keel.es)是用Java语言编写的，非常适合使用进化计算进行数据挖掘。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1944850|entityMap|0|LINK|mutability|MUTABLE|url|http://keel.es/^0|6|E|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

KEEL (<a href="http://keel.es" rel="nofollow">http://keel.es</a>) is written in Java and is good for using evolutionary computation for data mining.

blocks|key|2646461|text|看看由JMLR维护的用于机器学习的开源软件列表。你可以在这里找到它：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2646462|http://mloss.org/software/|offset|length|2646463|http://jmlr.csail.mit.edu/mloss/|2646464|它们代表了最先进的技术！|2646465|我对Weka的问题是，其中的一些算法已经过时了。|2646466|entityMap|0|LINK|mutability|MUTABLE|url|1^0|0|0|Q|0|0|0|W|1|0|0|0^^$0|@$1|2|3|4|5|6|7|T|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|U|8|@]|9|@$D|V|E|W|1|X]]|A|$]]|$1|F|3|G|5|6|7|Y|8|@]|9|@$D|Z|E|10|1|11]]|A|$]]|$1|H|3|I|5|6|7|12|8|@]|9|@]|A|$]]|$1|J|3|K|5|6|7|13|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|14|8|@]|9|@]|A|$]]]|M|$N|$5|O|P|Q|A|$R|C]]|S|$5|O|P|Q|A|$R|G]]]]

Have a look at list of Open Source software's for Machine learning maintained by JMLR.
you can find it here:

<a href="http://mloss.org/software/" rel="nofollow noreferrer">http://mloss.org/software/</a>

<a href="http://jmlr.csail.mit.edu/mloss/" rel="nofollow noreferrer">http://jmlr.csail.mit.edu/mloss/</a>

They represent State of Art!

My issue with Weka is that a number of algorithms in it are outdated.

blocks|key|4760023|text|我相信RapidMiner是一个很好的工具，应该添加到这个列表中。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4760024|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

i believe RapidMiner is an excellent tool that should be added to this list.

blocks|key|2646723|text|WEKA+(已经提到)，Orange+(http://orange.biolab.si/)，Tanagra+(http://data-mining-tutorials.blogspot.com)你可以在那里找到很好的教程。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2646724|是非常好的数据挖掘工具。|2646725|entityMap|0|LINK|mutability|MUTABLE|url|http://orange.biolab.si/|1|http://data-mining-tutorials.blogspot.com/^0|K|O|0|1J|15|1|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@$A|Q|B|R|1|S]|$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|X|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]]]

WEKA (Already mentioned),
Orange (http://orange.biolab.si/),
Tanagra (http://data-mining-tutorials.blogspot.com) you can find good tutorials there.

Are very good tools for data mining.

blocks|key|1939156|text|你可以检查我的软件，。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1939157|它是一个开源的Java软件，提供了70多种算法，用于：|1939158|1939159|频繁项集挖掘、|unordered-list-item|1939160|关联规则挖掘、|1939161|序列模式mining|1939162|sequential规则挖掘、|1939163|等..|1939164|1939165|entityMap^0|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|A|$]]|$1|E|3|F|5|G|7|V|8|@]|9|@]|A|$]]|$1|H|3|I|5|G|7|W|8|@]|9|@]|A|$]]|$1|J|3|K|5|G|7|X|8|@]|9|@]|A|$]]|$1|L|3|M|5|G|7|Y|8|@]|9|@]|A|$]]|$1|N|3|O|5|G|7|Z|8|@]|9|@]|A|$]]|$1|P|3|-4|5|6|7|10|8|@]|9|@]|A|$]]|$1|Q|3|-4|5|6|7|11|8|@]|9|@]|A|$]]]|R|$]]

You could check my software, the <a href="http://www.philippe-fournier-viger.com/spmf/" rel="nofollow">SPMF data mining framework</a>.

It is an open-source Java software that offers more than 70 algorithms for:

<ul>
<li>frequent itemset mining,</li>
<li>association rule mining,</li>
<li>sequential pattern mining</li>
<li>sequential rule mining.</li>
<li>and more..</li>
</ul>

blocks|key|33504|text|Pentaho是一个非常专业的解决方案。这绝对是一个非常好的选择。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|33505|entityMap|0|LINK|mutability|MUTABLE|url|http://www.pentaho.com/^0|0|7|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

<a href="http://www.pentaho.com/" rel="nofollow noreferrer">Pentaho</a> is a very professional solution. Definitely a very good choice.

blocks|key|2646376|text|你可以看看Data+Mining+SDK和它的blog。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2646377|entityMap|0|LINK|mutability|MUTABLE|url|http://datamining.codeplex.com/|1|http://msug.vn.ua/blogs/datamining/^0|5|F|0|N|4|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

You can look at <a href="http://datamining.codeplex.com" rel="nofollow noreferrer">Data Mining SDK</a> and its <a href="http://msug.vn.ua/blogs/datamining/" rel="nofollow noreferrer">blog</a>.

blocks|key|4759905|text|此处列出了一些开源数据挖掘工具：http://dataminingtools.net/browse.php|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4759906|entityMap|0|LINK|mutability|MUTABLE|url|http://dataminingtools.net/browse.php^0|G|11|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

A list of some open source data mining tools are listed here:
<a href="http://dataminingtools.net/browse.php" rel="nofollow noreferrer">http://dataminingtools.net/browse.php</a>

blocks|key|4759964|text|Eclipse+BIRT+http://www.eclipse.org/birt/phoenix/project/description.php|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4759965|entityMap|0|LINK|mutability|MUTABLE|url|http://www.eclipse.org/birt/phoenix/project/description.php^0|D|1N|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Eclipse BIRT <a href="http://www.eclipse.org/birt/phoenix/project/description.php" rel="nofollow noreferrer">http://www.eclipse.org/birt/phoenix/project/description.php</a>

blocks|key|33562|text|我相信KNIME也应该加入这个列表。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|33563|entityMap|0|LINK|mutability|MUTABLE|url|http://www.knime.org/^0|3|5|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I believe <a href="http://www.knime.org/" rel="nofollow noreferrer">KNIME</a> deserves to join this list as well.

blocks|key|2646598|text|Weka在分类和/machine学习方面很强大。对许多人来说，这被认为是人工智能的一部分，而不是实际的数据挖掘。RapidMiner在很大程度上也是这样的，但它的UI要好得多。Pentaho是Weka+AFAICT的专业支持。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2646599|你可能想看看ELKI，http://elki.dbs.ifi.lmu.de/，它是一个类似的项目，专注于聚类算法和离群值检测，这是数据挖掘的另外两个关键任务。|offset|length|2646600|entityMap|0|LINK|mutability|MUTABLE|url|http://elki.dbs.ifi.lmu.de/^0|0|B|R|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

Weka is strong for classification and /machine learning/. To many, this is considered to be more a part of artificial intelligence than of actual data-mining. RapidMiner is largely along the same lines, but with a much nicer UI. Pentaho is the professional support for Weka AFAICT.

You might want to have a look at ELKI, <a href="http://elki.dbs.ifi.lmu.de/" rel="nofollow">http://elki.dbs.ifi.lmu.de/</a> which is a comparable project that focuses on clustering algorithms and outlier detections, two other key tasks of data-mining.

blocks|key|4759924|text|您可以查看一下数据挖掘工具weka|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4759925|这里有一个关于WEKA教程的教程和视频集合的链接：http://www.dataminingtools.net/browsetutorials.php?tag=weka|offset|length|4759926|视频：http://www.dataminingtools.net/videos.php?id=6|4759927|entityMap|0|LINK|mutability|MUTABLE|url|http://www.dataminingtools.net/browsetutorials.php?tag=weka|1|http://www.dataminingtools.net/videos.php?id=6^0|0|P|1N|0|0|3|1A|1|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@$D|T|E|U|1|V]]|A|$]]|$1|F|3|G|5|6|7|W|8|@]|9|@$D|X|E|Y|1|Z]]|A|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|I|$J|$5|K|L|M|A|$N|O]]|P|$5|K|L|M|A|$N|Q]]]]

you can take a look at data mining tool, weka

Here is a link to a collection of tutorials and videos on WEKA
Tutorials:<a href="http://www.dataminingtools.net/browsetutorials.php?tag=weka" rel="nofollow noreferrer">http://www.dataminingtools.net/browsetutorials.php?tag=weka</a> 

Videos:
<a href="http://www.dataminingtools.net/videos.php?id=6" rel="nofollow noreferrer">http://www.dataminingtools.net/videos.php?id=6</a>

blocks|key|2646559|text|除了这些工具，我强烈建议学习Python和R。这些语言在分析过程中帮助很大。此外，还可以对大型数据集进行“自定义分析”。您也可以使用Javascript创建自己的自定义仪表板(查看numerous+charting+and+visualization+libraries)|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|2646560|entityMap|0|LINK|mutability|MUTABLE|url|http://blizzardzblogs.blogspot.com/2010/12/data-visualization-charts-and.html^0|2I|19|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Along with the tools, i would strongly suggest learning Python and R. These languages help a lot during analysis. Also, large datasets can be 'custom-analysed'. You might also create your own custom dashboard using Javascript(check out the <a href="http://blizzardzblogs.blogspot.com/2010/12/data-visualization-charts-and.html" rel="nofollow">numerous charting and visualization libraries</a>)

blocks|key|1938936|text|我自己就是一名蟒蛇猎手，我不得不说：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1938937|是!所有这些都可以在Python中完成。|1938938|我上一次玩的是美汤。这是一个非常简单易用的模块，可以让你从html和xml中抓取/挖掘数据(非常适合‘屏幕抓取’)。|1938939|如果你不懂python，..。嗯，它真的很容易学习。|1938940|0|offset|length|1938941|entityMap|LINK|mutability|MUTABLE|url|http://www.crummy.com/software/BeautifulSoup/^0|0|0|0|0|0|1|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|T|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|U|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|V|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|W|8|@]|9|@$J|X|K|Y|1|Z]]|A|$]]|$1|L|3|-4|5|6|7|10|8|@]|9|@]|A|$]]]|M|$I|$5|N|O|P|A|$Q|R]]]]

I am a python-er myself and I have to say:

Yes! All of that can be done in Python.

I last played around with Beautiful Soup[0]. It's a really simple to use module that lets you grab/mine data from html and xml (excellent for 'screen scraping').

If you dont know python, .... well It's really easy to learn.

[0]<a href="http://www.crummy.com/software/BeautifulSoup/" rel="nofollow noreferrer">http://www.crummy.com/software/BeautifulSoup/</a>

I'm due to take up a project which is into data mining. Before I jump in I wanted to probe around for different data mining tools (preferably open source) which allows web based reporting. In my scenario the data would be provided to me, so I'm not supposed to crawl for it.

In a nutshell, I am looking for a tool which does - Data Analysis, Web based Reporting, provides some kind of a dashboard and mining features.

I have worked on the Microsoft Analysis Services and BOXI and off late I have been looking at Pentaho, which seems to be a good option.

Please share your experiences on any such tool which you know of.

cheers

Data Mining open source tools

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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