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KDnuggets:Polls:数据挖掘工具的选用(May 2005) |
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数据挖掘者 发表于 2005/7/3 13:35:06 |
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IDMer总结：在商用领域的数据挖掘工具选择中，SPSS和SAS占据了统治地位（特别是针对中高端的商用项目）；Microsoft SQL Server领先于Oracle、IBM等挖掘工具的确让人有点出乎意料（估计还是在比较小的项目里会选用）；Excel占据了较大份额一方面是由于它过于流行易于掌握，另一方面其可编程性（通过VBA）应该是开发人员选用它的最大原因。在研究领域，自己开发程序可以寻求算法上的改进和突破，S-Plus、Statistica、Weka、MATLAB等等都是不错的选择。我不太熟悉CART/MARS/TreeNet/RF，有哪位了解它的请在本贴留言介绍一下。以下内容引自KDnuggets（http://www.kdnuggets.com/polls/2005/data_mining_tools.htm）：KDnuggets : Polls : Data Mining Tools You Used in 2005 (May 2005)
Poll
Data mining/Analytic tools you used in 2005 [376 voters, 860 votes total]
SPSS Clementine
500)this.width=500'> 135
SPSS
500)this.width=500'> 96
Excel
500)this.width=500'> 78
CART/MARS/TreeNet/RF
500)this.width=500'> 69
SAS
500)this.width=500'> 53
SAS Enterprise Miner
500)this.width=500'> 49
Your own code
500)this.width=500'> 39
Other free tools
500)this.width=500'> 34
Insightful Miner/ S-Plus
500)this.width=500'> 32
Statsoft Statistica
500)this.width=500'> 30
Weka
500)this.width=500'> 30
ThinkAnalytics
500)this.width=500'> 26
C4.5/C5.0/See5
500)this.width=500'> 25
R
500)this.width=500'> 25
Microsoft SQL Server
500)this.width=500'> 23
Other commercial tools
500)this.width=500'> 23
MATLAB
500)this.width=500'> 16
Mineset (PurpleInsight)
500)this.width=500'> 16
Xelopes
500)this.width=500'> 16
Oracle Data Mining
500)this.width=500'> 10
Gornik
500)this.width=500'> 8
KXEN
500)this.width=500'> 7
IBM Iminer
500)this.width=500'> 5
Angoss
500)this.width=500'> 3
Equbits
500)this.width=500'> 3
Fair Isaac
500)this.width=500'> 3
GhostMiner
500)this.width=500'> 3
Megaputer
500)this.width=500'> 3
CommentsThe numbers above represent the actual number of votes. Percentage will differ depending on whether it is computed relative to number of responders or number of votes.
Editor, Tool prices Tool prices tend to change, and differ for business and academic users (which sometimes can get a free license for research). With these caveats, the above tools can be grouped into these broad categories, according to an estimated price for business users as of May 2005.
Very Expensive, Enterprise-level: (over US $10,000) Fair Isaac, IBM, Insightful, Oracle, SAS, and SPSS
Expensive, Department-level: (from $1,000 to $9,999) Angoss, CART/MARS/TreeNet/Random Forests, Equbits, GhostMiner, Gornik, KXEN, Mineset, MATLAB, Megaputer, Microsoft SQL Server, Statsoft Statistica, ThinkAnalytics
Inexpensive, Personal-level: (from $1 to $999) Excel, See5
Free: C4.5, R, Weka, Xelopes |
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回复:KDnuggets:Polls:数据挖掘工具的选用(May 2005) |
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wagb(游客)发表评论于2007/8/8 4:31:51 |
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请问sas如何实现random forest 算法 谢谢！ |
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