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[BooksDataMiningUsingSasEnterpriseMinerACaseStudyApproac

Description: SAS软件EM模块教程Data Mining Using Sas Enterprise Miner - A Case Study Approach-SAS software module EM tutorial Data Mining Using Sas Enterprise Miner- A Case Study Approach
Platform: | Size: 1415168 | Author: | Hits:

[OtherdatamininginSAS

Description: 数据挖掘之类的电子书, 数据挖掘在SAS中的应用-Applying Data Mining Techniques Using Enterprise Miner™ Course Notes was developed by Sue Walsh. Some of the course notes is based on material developed by Will Potts and Doug Wielenga. Additional contributions were made by John Amrhein, Kate Brown, Iris Krammer, and Bob Lucas. Editing and production support was provided by the Curriculum Development and Support Department.
Platform: | Size: 4141056 | Author: LJ | Hits:

[ERP-EIP-OA-PortalSAS_Enterprise_Miner_Manual

Description: 做过数据挖掘的,应该对SAS不会陌生。这是SAS 9.0.1中Enterprise Miner的使用手册。即使没有SAS可以使用,通过该手册能够很好地了解做数据挖掘的步骤。-SAS will not be unfamiliar to those who have taken data mining expriments. This is the manual of Enterprise Miner module of SAS 9.0.1. Despite you don t have a SAS software, you can also have a very good understanding of the steps to do data mining through the manual.
Platform: | Size: 9619456 | Author: Joyce | Hits:

[Other Databasesattributes

Description: SAS Enterprise Miner”进行聚类分析-SAS Enterprise Miner " cluster analysis
Platform: | Size: 3072 | Author: 陈春燕 | Hits:

[Software EngineeringSAS-Data-Mining-Using-Sas-Enterprise-Miner---A-Ca

Description: SAS Data Mining book. A very good one for beginners, with case study.
Platform: | Size: 1416192 | Author: Leo Kieu | Hits:

[Other主成分分析

Description: 通过实例来研究SAS软件中的因子分析和主成分分析及二者分析结果的比较。以2012年城镇消费支出资料(数据来源于2013年《中国统计年鉴》)为依据,对全国31个省市进行主成分分析和因子分析,31个省市消费支出指标为X_1—食品,X_2—衣着,X_3—家庭设备及用品,X_4—医疗保健,X_5—交通通信,X_6—文教娱乐,X_7—居住,X_8其他商品和服务。(The factor analysis and principal component analysis of SAS software and the comparison between them are studied by examples. Town in 2012 consumer spending data (data from China statistical yearbook, 2013), on the basis of 31 provinces and cities nationwide, principal component analysis and factor analysis in 31 provinces and cities consumer spending index for X_1 - food, X_2 - clothing, X_3, household equipment and supplies, X_4 - health care, X_5 - traffic communication, X_6 - cultural and educational entertainment, X_7 - living, X_8 other goods and services.)
Platform: | Size: 11264 | Author: zwl666 | Hits:

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