What's New in SAS Enterprise Miner 6.1 发表评论(0) 编辑词条
What's New in SAS Enterprise Miner 6.1
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Overview
SAS Enterprise Miner 6.1 is a major new release of data mining tools for use with SAS 9.2. The scope of improvements includes many analytical and deployment functionality enhancements, as well as changes that were made to integrate the Enterprise Miner tool set with the SAS 9.2 system.
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SAS 9.2 Platform
The SAS 9.2 system is an improved platform for managing and deploying analytical and business intelligence applications for both single-user applications and multi-user enterprises. SAS Enterprise Miner 6.1 contains changes related to the SAS 9.2 system that improve SAS Enterprise Miner installation, security, and administration.
Software Versions and Migration
SAS Enterprise Miner 6.1 requires the SAS 9.2 Platform release.
SAS Enterprise Miner 5.3 will not operate with SAS 9.2.
If you have existing SAS Enterprise Miner 5.3 project information stored in your SAS Metadata Server, the project information will be converted from SAS 9.1.3 format to SAS 9.2 format during the SAS 9.2 / SAS Enterprise Miner 6.1 installation.
If you have existing SAS Enterprise Miner 5.3 project data folders that are stored on SAS Workspace Servers, the project data folders do not require conversion for use with SAS 9.2 and SAS Enterprise Miner 6.1. All SAS Enterprise Miner 5.3 project data folders, files, tables, views, and catalogs that are stored on SAS Workspace Servers are compatible for use with SAS 9.2 and SAS Enterprise Miner 6.1.
SAS Enterprise Miner 6.1 users can open existing SAS Enterprise Miner 5.3 projects without any manual conversion process.
SAS Enterprise Miner 6.1 projects cannot be converted for use with SAS Enterprise Miner 5.3.
SAS Enterprise Miner 4.3 users who wish to upgrade project data for use with SAS Enterprise Miner 6.1 can use the SAS Enterprise Miner project conversion macro. The project conversion macro upgrades SAS Enterprise Miner 4.3 project structures to SAS Enterprise Miner 5.3 project structures. SAS Enterprise Miner 6.1 opens SAS Enterprise Miner 5.3 project structures by the SAS Enterprise Miner Project conversion macro.
Projects
SAS Enterprise Miner 6.1 project information is now stored and managed in the SAS Metadata Folders. SAS Enterprise Miner 6.1 users create projects in a specific folder location.
The default location for new SAS Enterprise Miner 6.1 projects is My Folder. The My Folder location is unique for every user and is a private location. When a SAS Enterprise Miner 6.1 user creates a project, the user can accept the default project location, or specify a different folder of their own preference. For example, a user or group of users might store mining projects in a common folder where the projects can be shared.
SAS Enterprise Miner 6.1 users will open projects by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
When the SAS Metadata Server is upgraded from SAS 9.1.3 to SAS 9.2, existing SAS Enterprise Miner 5.3 project information that was stored in the SAS Metadata Server is migrated to the Shared Data folder.
SAS administrators can view SAS Enterprise 6.1 project information via the SAS Management Console.
Models
SAS Enterprise Miner 6.1 models are stored and managed in the SAS Metadata Folders. SAS Enterprise Miner 6.1 users register models to a specific folder location.
SAS Enterprise Miner 6.1 users may now open or import models by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
When the SAS Metadata Server is upgraded from SAS 9.1.3 to SAS 9.2, existing SAS Enterprise Miner 5.3 models that were stored in the SAS Metadata Server are migrated to the Shared Data folder.
SAS administrators can view SAS Enterprise 6.1 model information via the SAS Management Console.
SAS Management Console Plug-in
The SAS Enterprise Miner 6.1 Plug-in for the SAS Management Console is revised for SAS 9.2, but maintains the same range of functionality as in SAS 9.1.3. For more information, see the SAS Enterprise 6.1 Reference Help chapters on Installation and Configuration for more information.
SAS administrators can use the SAS Management Console to view SAS Enterprise Miner project information.
Java Versions
SAS administrators retain the ability to deliver SAS Enterprise Miner 6.1 to users via Java Web Start. Java Web Start users should have Java 1.5.12 or a compatible version.
Installed versions of SAS 9.2 include Java 1.5.12. No further version of Java is required.
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Usability
SAS Enterprise Miner 6.1 provides the following improvements in usability:
Summary Statistics in Variable List Tables
The variable list tables that SAS Enterprise Miner users are familiar with have been improved in SAS Enterprise Miner 6.1. The variable view tables that surface in locations throughout the software now provide users with summary statistics for the table variables.
The summary statistics are computed by the Advanced Advisor function in the Data Source Wizard, by the Input Data node, and by the Stat Explore node. Variable summary statistics are often used to make decisions about how to treat variables in data mining models.
Configurable Attributes in Variable List Tables
SAS Enterprise Miner 6.1 is capable of displaying many different variable attribute columns in SAS Enterprise Miner variable list tables. Instead of displaying enormous tables that have many variable attribute columns, SAS Enterprise Miner 6.1 enables users to configure variable list table displays by selecting only the variable attributes that are important to their work.
Quick Text Search for SAS Code Editors and Text Viewers
The SAS Code editors and text viewers have been enhanced with a quick text search toolbar that highlights and navigates between selected text search results. This is a great aid when searching for text in SAS Code, the SAS Log, and SAS Output listings.
You can launch Quick Text Search from the SAS Enterprise Miner 6.1 main menu, or use to access the new tool bar.
Interactive Graphics Samples
Previous versions of SAS Enterprise Miner provided interactive exploratory graphics that used a quick sample of the values in a variable list table. In SAS Enterprise Miner 6.1, the quick table sample that the software performs to generate interactive graphics has been improved.
The new quick sample method scans only the attribute columns that the user selects, plus any additional Target, ID, Frequency, or Cost variables. This capability reduces the number of columns needed to perform interactive graphic sampling and increases the number of rows of data that are available for graphics.
Variable table list sampling for interactive graphics can now be performed by using a sampling algorithm that is stratified by categorical target variables. This change improves the representation of the sample in the presence of skewed data.
Project Start and Stop Code
The Project Start Code Editor window is modified to include the SAS log. Convenient access to the SAS log helps users who need to debug or modify their SAS Enterprise Miner project start code.
The Project End Code Editor window has been eliminated.
SAS Library Explorer
The SAS Library Explorer has been enhanced to view and edit (when appropriate) catalog entries of the types SOURCE, LOG, OUTPUT, and XML.
Model Import and Export
SAS Enterprise Miner 6.1 users can register models directly to the SAS Metadata Folders tree structure. This feature provides users with more control over the security, access privileges, and organization of models.
SAS Enterprise Miner 6.1 users can import a registered model into an existing data mining process flow diagram by using the Model Import node. The score code of the imported model is applied to the data in the process flow diagram, generating new model assessment statistics.
The Model Repository window has been removed from SAS Enterprise Miner 6.1. The former flat list of registered models has been replaced by a hierarchical view of models in the SAS Metadata Folders. The Model Import node provides SAS Enterprise Miner 6.1 users with a list of available models.
SAS Enterprise Miner 6.1 users can select File Open Model from the main menu to open a file utility window to browse the SAS Metadata Folders tree structure and choose a model for inspection.
SAS Enterprise Miner 6.1 users can also use the Model Import tool to navigate the SAS Metadata Folders tree structure and choose a model for addition to the process flow diagram.
Interactive Decision Tree
A switch-targets feature has been added to SAS Enterprise Miner 6.1 so that users can select a new dependent variable in a tree leaf and make new splits based on the new target. This is a powerful analytical feature for users who design decision trees for segmentation strategies.
The Interactive Decision Tree is fully integrated into SAS Enterprise Miner 6.1 and requires no separate installation or documentation.
SAS Enterprise Miner 6.1 gives users who start the software using Java Web Start users full use of the Interactive Decision Tree.
The former Tree Desktop Application that was associated with prior releases of SAS Enterprise Miner is not distributed with SAS Enterprise Miner 6.1, but is available on the SAS downloads Web page for legacy purposes.
The Tree Desktop Application will not work with a SAS 9.2 server.
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New Nodes
SAS Enterprise Miner 6.1 includes two new data mining nodes. The new nodes are presented using the SEMMA functional groupings of Enterprise Miner.
Sample — SAS Enterprise Miner 6.1 adds the following new node to the Sample tab of the Enterprise Miner tool bar:
File Import node — The File Import node enables users to directly integrate external data files into SAS Enterprise Miner 6.1 process flow diagrams. The external file types supported include dBase .DBF files, Stata .DTA files; Microsoft Excel .XLS files; SAS .JMP files; Paradox .DB files; SPSS .SAV files; Lotus .WK1, .WK3, and .WK4 files; as well as tab-delimited .TXT files; comma-delimited .CSV files; and user-defined delimited .DLM files. Data files to be imported must be located either on the SAS Enterprise Miner client machine or in a network location that is accessible to the SAS Enterprise Miner server or the SAS server system.
Model — SAS Enterprise Miner 6.1 adds the following new node to the Model tab of the Enterprise Miner tool bar:
LARS — The LARS node uses Least Angle Regression and LASSO algorithms from the SAS/STAT procedure GLMSELECT to perform model fitting tasks and sophisticated variable selection for interval target models.
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Enhanced Nodes
The following nodes in SAS Enterprise Miner 6.1 were enhanced in functionality or reorganized into new Enterprise Miner tool groups. The enhanced and changed nodes are presented using the SEMMA functional groupings of Enterprise Miner.
Sample — The following changes have been made to the Sample tools in Enterprise Miner 6.1:
Append node — The Append node enables you to concatenate two data sets together. In SAS Enterprise Miner 6.1, the Append node is able to combine training, validation, and test data sets into a single training data set for the purpose of computing full data statistics.
Explore — The following changes have been made to the Explore tools in Enterprise Miner 6.1:
Association node — The Association node is used to identify frequently occuring association and sequence patterns in transactional data. In SAS Enterprise Miner 6.1, the Association node improves by using a new SAS data mining procedure called MBSCORE. MBSCORE produces faster and more accurate output than previous versions of the Association node.
Stat Explore node — The Stat Explore node is used to generate summary statistics for data exploration. In SAS Enterprise Miner 6.1, the Stat Explore node computes summary statistics on validation and test data as well as the train data. Most Stat Explore results plots have been updated to show validation and test results. Stat Explore provides new plots that can compare variable distributions across multiple categorical targets and by-group segments.
Graph Explore node — The Graph Explore node is an advanced visualization tool for interactive data exploration. In SAS Enterprise Miner 6.1, the Graph Explore node can generate samples that are stratified by categorical target variables.
Modify — The following changes have been made to the Modify tools in Enterprise Miner 6.1:
Drop node — The Drop node is used to remove variables from metadata, SAS tables, and SAS views. In SAS Enterprise Miner 6.1, the Drop node works on data sources other than train tables. For example, in SAS Enterprise Miner 6.1, the Drop node can be used on transaction tables.
Model — The following changes have been made to the Model node tools in Enterprise Miner 6.1:
AutoNeural node — The AutoNeural node is used to automatically search for a Neural Network topology. The SAS Enterprise Miner 6.1 AutoNeural node adds a Target Layer Error Function property that permits a wider variety of distributions to be fitted. The AutoNeural node also adds a new final training phase that further refines the model after the topology has been selected.
Decision Tree node — The Decision Tree node builds statistical decision trees for predictive modeling. The SAS Enterprise Miner 6.1 Decision Tree node contains a new integrated interactive Decision Tree model building utility. Multiple target variables are supported for Interactive Decision Tree designs. Only one target is be used for model assessment statistic calculations. You can also use a Model Import node to select a different target variable and to generate model assessment statistics. Lastly, the default value for the SAS Enterprise Miner 6.1 Decision Tree sample sizes has been changed to 20,000.
Model Assessment Statistics — The model assessment statistics modules in SAS Enterprise Miner modeling nodes and in the model comparison node compute rank order statistics such as lift, captured response, and ROC. In SAS Enterprise Miner 6.1, a new algorithm provides faster and more accurate model assessment results. Some users might observe minor differences in the model assessment measurements when the analyzed data contains large proportions of observations that have tied probabilities. See the SAS Enterprise Miner Reference Help chapter on the Model Comparison node for more information about model assessment statistics.
Model Import node — The Model Import node imports registered models and models that were not created using SAS Enterprise Miner into the SAS Enterprise Miner 6.1 environment. The score code of the saved model is applied to the data that is used in the process flow diagram and new model assessment statistics are generated.
You can use the Model Import node to compare registered models to newly developed models, or to apply registered model score code to new data sets. The Model Import node and the File Import node can be used together to enable users to compare models across different projects and data sources.
Neural Network node — The Neural Network node creates feed forward networks for predictive models. The SAS Enterprise Miner 6.1 Neural Network node contains a new Weight Decay property that has an initial value of 0.0. Non-zero values for the Weight Decay property will penalize the growth of weights in the neural network, and sometimes they are used to limit overfitting in the absence of validation data. The Neural Network node Properties Panel has also been reorganized for improved usability.
Rule Induction node — The Rule Induction node builds predictive models based on incrementally identifying true cases in the data. In SAS Enterprise Miner 6.1, the default maximum number of target levels to be modeled in the Rule Induction node is increased from 32 to 1024. The increase in the maximum number of target levels facilitates the modeling of problems with high cardinality.
Assess — The following changes have been made to the Assessment node tools in Enterprise Miner 6.1:
Model Comparison node — The Model Comparison node generates comparative statistics and then automatically or manually selects a champion model from the contender models. In SAS Enterprise Miner 6.1, the Model Comparison node can compute or recompute statistics for train, validation, and test data sets. This capability is useful when model data has been modified and new model fit statistics are needed. Use the Model Comparison node together with the Append node to partition training data in order to perform model selection, and then recombine the data and compute fit statistics for the full data. The full data fit statistics are useful for model comparison purposes.
Score node — The Score node aggregates score code from the process flow diagram to create a single, deployable score code object. In SAS Enterprise Miner 6.1, the Score node scans and manipulates the SAS score code that the process flow diagram generates in order to eliminate intermediate code that produces terms that are not deployed in the final model function. The internally manipulated code is called optimized score code. The Score node now creates optimized score code by default. The Score node can also output the nonoptimized score code for comparison.
For example, the Imputation node can add SAS code that creates many new variables, but a subsequent model selection step may keep only a few of the new terms. The optimized code eliminates unused terms that were created by the Imputation node.
The optimized code will have a major positive impact on scoring and deployment processes. Fewer variables will need to be saved in the score input data sets in operational systems, which can save enterprises large amounts of resources and labor.
Utility — The following changes have been made to the Utility node tools in Enterprise Miner 6.1:
Metadata node — The Metadata node modifies the variable information, or metadata, that is passed on to subsequent tools in a process flow diagram. In SAS Enterprise Miner 6.1, you can select a single source of data and metadata for each variable table role. For example, if you have a process flow diagram with three branches, you can use the Metadata node to select a training table for one branch, a validation table for another branch, and a test table for the third branch.
The Metadata node improvements also let you modify the metadata for individual variables in each table role. This function is useful when creating jobs that process many tables. Metadata node users can also merge metadata from multiple sources. Merging metadata from multiple sources is useful when aggregating the results from multiple variable selection strategies.
For example, consider the task of combining the results of terms that were selected by a stepwise selection algorithm and a decision tree algorithm. You can retain terms that were selected by a single model, terms that were selected by a majority of models, or terms that were selected by all models. This capability provides users with a large degree of control over model creation strategies.
Reporter node — The Reporter node generates PDF and RTF documents for archiving and reporting. In SAS Enterprise Miner 6.1, the Reporter node provides new SAS ODS (Output Delivery System) functions. The new functions create document graphs, process flow diagrams, and analytical plots that match the graphics that are displayed in the SAS Enterprise Miner user interface.
The SAS Enterprise Miner 6.1 Reporter node also provides new Decision Tree results plots for use in PDF and RTF documents. In Reporter node output, the properties list for each node tool indicates the property settings that have been changed from their default values. The Reporter results window now contains a standard external file viewer that you can use to view the PDF or RTF document that was produced.
Credit Scoring — The following changes have been made to the add-on Credit Scoring node tools of Enterprise Miner 6.1:
Interactive Grouping node — The Interactive Grouping node creates and manages the grouping of raw values into modeling terms. In SAS Enterprise Miner 6.1, the Interactive Grouping node provides improved support for special code mappings; treats interval variables that have limited numbers of values as interval variables rather than categorical variables; and adds new properties that control the binning method and the number of fine detail bins.
Scorecard node — The Scorecard node builds predictive models from scorecard functions. In SAS Enterprise Miner 6.1, the Scorecard node contains several new configurable properties. The new Model Ordering property specifies the order of terms that were entered into the regression equation model selection search. New Stay, Stop, and Force properties have been added to enhance the model selection search.
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Extension Tool Programming
In Enterprise Miner 6.1, the Extension Tool Programming interface has been updated and significantly enhanced. For more information about the SAS Enterprise Miner 6.1 Extension Tool Programming Guide, see the product documentation page for SAS Enterprise Miner at http://support.sas.com.
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Copyright © 2009 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
最新的SAS企业矿工6.1
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概览
SAS企业矿工6.1是主要的开采使用的工具与新的数据发布的SAS 9.2。在改善的范围包括了许多分析和部署功能增强，以及所做整合企业Miner工具的SAS 9.2的系统设置改变。
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平台的SAS 9.2
在SAS 9.2系统是一种用于管理和部署平台的分析和改进为单用户的应用和多用户企业商业智能应用。 SAS企业矿工6.1包含了有关的SAS 9.2系统，改善矿工的SAS企业安装，安全性变更和管理。
软件版本和迁移
SAS企业矿工6.1要求的SAS 9.2平台版本。
SAS企业矿工5.3将无法运行使用SAS 9.2。
如果您现有的SAS企业矿工5.3项目储存在你的的SAS元数据，项目信息将在9.1.3格式的SAS到SAS 9.2格式在转换的SAS 9.2服务器/ SAS企业矿工6.1安装。
如果您现有的SAS企业矿工5.3项目上的数据的SAS工作区服务器，存储数据文件夹的项目不需要使用与SAS 9.2和SAS企业矿工6.1转换文件夹。所有矿工5.3 SAS企业项目数据文件夹，文件，表，视图，并基于服务器上存储的SAS工作区目录兼容使用与SAS 9.2和6.1 SAS企业矿工。
SAS企业矿工6.1用户可以打开，无需任何手动转换过程中存在的SAS企业矿工5.3项目。
SAS企业矿工6.1项目不能转换为使用SAS企业矿工5.3。
SAS企业矿工4.3用户谁希望升级使用SAS企业矿工6.1项目数据可以使用SAS企业矿工项目转换宏。该项目的升级转化宏观矿工4.3 SAS企业项目结构的SAS企业矿工5.3项目结构。 SAS企业矿工6.1开篇SAS企业矿工项目转换宏矿工5.3 SAS企业项目结构。
项目
SAS企业矿工6.1项目信息现在存储和管理的SAS元数据文件夹。 SAS企业矿工6.1用户创建在一个特定的文件夹位置的项目。
对新的SAS企业矿工6.1项目的默认位置是我的文件夹。我的文件夹的位置是独一无二的每个用户，是一个私人的位置。当矿工6.1 SAS企业用户创建一个项目，用户可以接受默认的项目位置，或指定一个他们自己的选择不同的文件夹。例如，一个用户或用户组可以存储在一个公共文件夹开采项目，其项目可以共享。
SAS企业矿工6.1用户将通过使用开放标准的打开文件窗口，显示的SAS元数据文件夹，默认情况下的树结构的项目。
当元数据服务器的SAS北欧航空公司9.1.3升级到SAS 9.2，现有的SAS企业矿工5.3项目信息，是我们在元数据服务器的SAS存储迁移到共享数据文件夹。
管理员可以查看的SAS通过管理控制台的SAS的SAS 6.1企业项目信息。
模型
SAS企业矿工6.1模型存储和管理的SAS元数据文件夹。 SAS企业矿工6.1用户注册模式，以一个特定的文件夹位置。
SAS Enterprise Miner 6.1 users may now open or import models by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
当元数据服务器的SAS北欧航空公司9.1.3升级到SAS 9.2，现有的SAS企业矿工在5.3元数据服务器的SAS存储模型迁移到共享数据文件夹。
管理员可以查看的SAS的SAS通过SAS企业级管理控制台6.1模型的信息。
的SAS管理控制台插件
SAS企业矿工为6.1插件的SAS管理控制台，是订正的SAS 9.2，而且保持了相同的功能在范围的SAS 9.1.3。有关更多信息，请参阅更多信息，SAS企业6.1安装和配置参考帮助章节。
管理员可以使用的SAS北欧航空公司管理控制台查看SAS企业矿工项目信息。
Java版本
管理员保留的SAS能够提供通过Java Web Start SAS企业矿工6.1给用户。 Java Web Start的用户都应该具有的Java 1.5.12或兼容的版本。
的SAS 9.2安装的版本，包括Java 1.5.12。没有进一步的Java版本是必需的。
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可用性
SAS企业矿工6.1可用性提供了以下改进：
概要统计变量名单表
在变量列表表SAS企业用户与矿工已在6.1 SAS企业改善矿工熟悉。鉴于该变量表表面的地点在整个软件现在提供的表变量汇总统计用户。
的汇总统计，计算由高级顾问函数在数据源向导，在输入数据节点，由统计探索节点。可变汇总统计经常被用来就如何对待数据挖掘模型变量的决定。
在可变名单表可配置属性
SAS企业矿工6.1能够显示在SAS企业矿工变量表列出许多不同的变量属性列。而不是显示有许多变量属性列巨大的表，SAS企业矿工6.1使用户能够设定变量列表表显示只选择那些他们工作的重要变量属性。
快速全文检索的SAS代码编辑器和文本观众
SAS的代码编辑器和文本观众都配备了快速的文本搜索工具，突出与所选的文本搜索结果中导航。这是一个伟大的援助文本搜索时，在SAS代码，SAS的日志，和SAS输出列表。
您可以从SAS企业矿工6.1主菜单，或使用可以进入新的工具栏的快速全文检索。
交互式图形样品
矿工的SAS企业提供互动的早期版本中所使用表变量列表的值快速样本探索图形。在SAS企业矿工6.1，快捷的表样，该软件执行产生互动图形已有所改善。
新的快速抽样方法只扫描属性列加任何额外的目标，身份证，频率，或成本变量，用户选择。该功能减少了所需的采样进行图形交互列数，增加了数据行数图形可用。
变量表列出交互式图形抽样现在可以通过使用采样算法，通过明确目标变量分层。此更改提高了中存在的扭曲的数据样本的代表性。
项目启动和停止码
该项目启动代码编辑器窗口的修改，以包括的SAS日志。方便地帮助用户的SAS日志谁需要调试或修改其SAS企业矿工项目启动代码。
在项目结束代码编辑器窗口已被消除。
图书馆资源管理器的SAS
SAS的图书馆资源管理器已得到增强，查看和编辑（在适当的时候）的类型目录条目的来源，日志，输出，和XML。
模型导入和导出
SAS企业矿工6.1用户可直接向登记模式的SAS元数据文件夹的树状结构。此功能提供了更多对用户的安全控制，访问权限，以及模型的组织。
SAS企业矿工6.1用户可以导入到现有的数据挖掘过程流程图通过模型导入节点注册的模特儿。在进口模型评分代码应用到工艺流程图中的数据，产生新的模式评估统计。
示范库窗口已被删除从SAS企业矿工6.1。前者单位的注册最多的车型名单已取代在文件夹的SAS元数据模型的分层视图。该模型导入节点提供SAS 6.1企业矿工的可用型号的用户。
SAS企业矿工6.1用户可以选择从主菜单文件打开模式打开文件浏览窗口工具的SAS元数据文件夹树结构，然后选择一个检查模式。
SAS企业矿工6.1用户还可以使用模型导入工具导航的SAS元数据文件夹树状结构，并选择了除工艺流程图模型。
互动决策树
阿开关的目标功能已被添加到SAS企业矿工6.1，使用户可以选择新的叶子在树上因变量，并就新的目标为基础的新的分裂。这是一个功能强大的分析功能，为用户谁设计的细分策略决策树。
互动决策树是完全集成到SAS企业矿工6.1，无需单独安装或文档。
SAS企业矿工6.1为用户提供了谁启动软件使用Java Web Start用户的互动，充分利用决策树。
前树桌面应用程序，是符合SAS企业矿工以前的版本是不相关的分布与SAS 6.1企业矿工，但基于SAS可供下载的Web页面遗产的目的。
树桌面应用程序将无法工作与SAS 9.2服务器。
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新节点
SAS企业矿工6.1包括两种新的数据挖掘的节点。新的节点提出利用企业集团的矿工SEMMA功能。
样品- SAS企业矿工6.1添加了以下新的节点企业的矿工工具栏样本标签：
文件导入节点-该文件导入节点使用户可以直接集成到SAS企业矿工外部数据文件6.1流程图。外部支持的文件类型包括的dBASE。DBF文件而言，Stata。差热分析的文件; Microsoft Excel中。XLS文件，SAS等。选配计划的文件;悖论。DB文件，酵素。SAV文件，莲花。周价格。WK3，和。WK4文件;为以及制表符分隔。TXT文件，逗号分隔的。CSV文件，和用户定义的分隔。DLM文件。数据文件输入必须是基于SAS企业矿工的客户机或网络中的位置，都可以访问企业矿工的SAS服务器或SAS服务器系统的位置。
模型- SAS企业矿工6.1添加了以下新的节点企业的矿工工具栏型号标签：
拉尔斯-拉尔斯节点使用的最角回归和从SAS拉索算法/转录过程GLMSELECT模型拟合来执行任务和复杂的间隔目标模型变量选择。
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增强节点
SAS企业级矿工在6.1以下节点的功能得到了加强，或到新的企业Miner工具集团重组。增强和改变节点提出了利用企业集团的矿工SEMMA功能。
示例-下面的更改已作出示例工具企业矿工6.1：
附加节点-追加节点，您可以连接两个数据集在一起。在SAS企业矿工6.1，追加节点能够结合训练，验证，并在单一培训的完整数据计算统计目的的一组数据测试数据集。
探索-以下修改过矿工6.1在企业的探索工具：
协会节点-协会节点是用来识别和频繁发生的关联交易中的数据序列模式。在SAS企业矿工6.1，该协会节点提高了使用新的SAS数据挖掘过程调用MBSCORE。 MBSCORE生产更快和更精确的输出比以前的版本协会节点。
统计探索节点-探索的统计节点用于生成汇总统计数据的探索。在SAS企业矿工6.1统计探索节点计算的验证和测试数据的汇总统计以及列车的数据。大多数统计探索的结果曲线已经经过更新以显示验证和测试结果。统计探索提供了新的阴谋，可以比较多个和明确的目标变量分布的组部分。
图探索节点-探索节点的图是一个先进的勘探交互式数据可视化工具。在SAS企业矿工6.1格拉夫探索节点可以生成样本，由分层明确目标变量。
修改-下列变更已在企业矿工6.1修改工具：
下降节点-在下拉节点用于去除数据变量的SAS表，和SAS的意见。在SAS企业矿工6.1拖放节点工程的数据源表比其他列车。例如，在SAS企业矿工6.1拖放节点可用于交易表。
模型-下面的更改已作出示范节点工具，在企业矿工6.1：
AutoNeural节点- AutoNeural节点用于自动寻找一个神经网络的拓扑结构。 SAS企业矿工6.1 AutoNeural节点添加了一个目标层误差函数的财产，允许更多的发行各种被套。该AutoNeural节点还增加了一个新的最后训练阶段，进一步细化后的拓扑结构已选定的模式。
决策树节点-决策树节点建立预测模型的统计决策树。 SAS企业矿工6.1决策树节点包含一个新的综合互动决策树模型的建立实用工具。多目标变量支持互动决策树设计。只有一个目标，可用于评估的统计模型计算。您也可以使用一个模型导入节点选择不同的目标变量，生成模式评估统计。最后，对矿工的SAS 6.1企业抽样规模决策树的默认值已更改为20000。
模型评估统计-统计模型评估模块的SAS企业矿工建模节点和节点的计算模型的比较，如电梯次第统计，被俘的反应，和中华民国。在矿工6.1 SAS企业，一个新的算法提供更快，更精确的模型评估的结果。有些用户可能会观察该模型评估测量小异的分析数据时，包含有密切联系的概率较大比例的意见。见SAS企业级示范比较有关模型评估统计信息节点矿工参考帮助篇章。
模型导入节点-节点的模型导入进口注册的模式，并没有把创建的SAS企业级矿工6.1环境SAS企业矿工模型。在保存的模型评分代码适用于所使用的程序流程图及评估的新模式产生的数据统计。
您可以使用节点的模型导入注册模式比较新发展模式，或申请注册的模特儿评分代码，新的数据集。该模型导入节点和文件导入节点可以一起使用，使用户能够比较不同的项目和数据源模型。
神经网络节点-神经网络节点的创造的前馈网络的预测模型。 SAS企业矿工6.1神经网络节点包含一个新的重量衰减属性，有一个初始值为0.0。非零重量衰减属性值会惩罚权重的神经网络的发展，有时它们被用来限制在验证数据的情况下过拟合。神经网络节点的属性面板也已改组，以提高可用性。
规则归纳节点-节点的规则归纳的基础上逐步确定了数据真实个案为基础的预测模型。在SAS企业矿工6.1的目标水平默认最大数量的规则归纳节点模型从32增加至1024。在目标水平的最大数量的增加促进了高基数问题建模。
评估-下列变更已在企业矿工6.1节点的评估工具：
型号比较节点-节点生成模型的比较比较统计数字，然后自动或手动选择从竞争者模型冠军模型。在SAS企业矿工6.1型号比较节点可以计算列车或重新计算，验证统计数据和测试数据集。这种能力是非常有用的模型数据已被修改，新的模型拟合统计量是必要的。使用该模型的比较节点与节点追加分区训练数据，以执行模式的选择，然后重组的数据和计算的全部数据拟合统计。完整的数据拟合统计为模型进行比较有用。
分数节点-节点的分数汇总评分从程序流程图的代码创建一个单一的，可部署的评分代码的对象。在SAS企业矿工6.1分数节点扫描和操纵SAS评分代码的程序流程图生成，以消除产生的中间代码是不会在最后模型函数部署条件。国内操纵的代码被称为优化评分代码。现在的分数节点优化创建默认评分代码。节点的分数也可以输出比较nonoptimized评分代码。
例如，归责节点可以增加SAS代码创建了许多新的变数，但随后的模型选择步骤可能只保留了一些新的条款。的优化代码消除的是由未使用的归责节点创建条件。
优化的代码对得分和部署过程重大，积极的影响。较少的变量将需要在分数输入数据业务系统，可以节省企业的资源和劳动力大量套保存。
实用-下面的更改已作出的实用工具，在企业节点矿工6.1：
元数据节点-元数据节点的修改变量信息，或元数据，即通过在工序流程图随后的工具。在SAS企业矿工6.1，你可以选择一个数据和每个变量表的作用元数据的单一来源。例如，如果您有三个部门的工艺流程图，您可以使用元数据节点选择一个分支，在另一分行验证表，第三个分支一个测试表的训练表。
元数据节点的改进也让您修改每个表中的作用个体变量元数据。此功能时非常有用创造就业机会的过程中的许多表。元数据节点用户还可以合并来自多个源的数据。合并来自多个源的数据时非常有用来自多个变量选择策略的结果。
例如，考虑相结合的，分别由一个逐步的选择算法和决策树算法的选择方面成果的任务。你可以保留，分别由一个单一的模式，即是由大多数的模型，或者是由所有型号选择条件选择条件选择条款。此功能提供了一种控制模型的创建策略很大程度上用户。
记者节点-记者节点生成PDF格式和存档和通报RTF文档。在SAS企业矿工6.1记者节点提供新的SAS消耗臭氧层物质（输出传送系统）功能。新的函数创建图形文件，工艺流程图，并分析阴谋，匹配的是SAS企业矿工用户界面中显示的图形。
SAS企业矿工6.1记者节点还提供了PDF和RTF文件，使用新的决策树结果阴谋。在记者节点的输出，每个节点的工具属性列表显示的财产已经从它们的默认值更改的设置。记者结果窗口现在包含一个标准的外部文件浏览器，您可以使用浏览PDF或RTF文档制作。
信用评分-以下变化作了一些附加的企业信用评估矿工6.1节点工具：
互动分组节点-互动分组节点创建和管理纳入模型计算的原始值分组。在SAS企业矿工6.1互动分组节点提供了改进的特殊代码映射支持，给予该有，而不是绝对的变量区间变量的值数量有限区间变量，并增加了新的属性，控制分块方法和一些细节垃圾箱。
记分卡节点-节点生成的记分卡的记分卡的功能预测模型。在SAS企业矿工6.1记分卡节点包含几个新的配置属性。新示范订购属性指定的条款顺序分为回归方程模型选择搜索输入。新的住宿，停止和部队属性已被添加到提高模型选择搜索。
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扩展编程工具
在企业矿工6.1，扩展工具编程接口已更新，显着提高。如需有关SAS企业矿工6.1扩展工具编程指南信息，请参阅SAS企业矿工在http://support.sas.com产品文档页面。
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Overview
SAS Enterprise Miner 6.1 is a major new release of data mining tools for use with SAS 9.2. The scope of improvements includes many analytical and deployment functionality enhancements, as well as changes that were made to integrate the Enterprise Miner tool set with the SAS 9.2 system.
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SAS 9.2 Platform
The SAS 9.2 system is an improved platform for managing and deploying analytical and business intelligence applications for both single-user applications and multi-user enterprises. SAS Enterprise Miner 6.1 contains changes related to the SAS 9.2 system that improve SAS Enterprise Miner installation, security, and administration.
Software Versions and Migration
SAS Enterprise Miner 6.1 requires the SAS 9.2 Platform release.
SAS Enterprise Miner 5.3 will not operate with SAS 9.2.
If you have existing SAS Enterprise Miner 5.3 project information stored in your SAS Metadata Server, the project information will be converted from SAS 9.1.3 format to SAS 9.2 format during the SAS 9.2 / SAS Enterprise Miner 6.1 installation.
If you have existing SAS Enterprise Miner 5.3 project data folders that are stored on SAS Workspace Servers, the project data folders do not require conversion for use with SAS 9.2 and SAS Enterprise Miner 6.1. All SAS Enterprise Miner 5.3 project data folders, files, tables, views, and catalogs that are stored on SAS Workspace Servers are compatible for use with SAS 9.2 and SAS Enterprise Miner 6.1.
SAS Enterprise Miner 6.1 users can open existing SAS Enterprise Miner 5.3 projects without any manual conversion process.
SAS Enterprise Miner 6.1 projects cannot be converted for use with SAS Enterprise Miner 5.3.
SAS Enterprise Miner 4.3 users who wish to upgrade project data for use with SAS Enterprise Miner 6.1 can use the SAS Enterprise Miner project conversion macro. The project conversion macro upgrades SAS Enterprise Miner 4.3 project structures to SAS Enterprise Miner 5.3 project structures. SAS Enterprise Miner 6.1 opens SAS Enterprise Miner 5.3 project structures by the SAS Enterprise Miner Project conversion macro.
Projects
SAS Enterprise Miner 6.1 project information is now stored and managed in the SAS Metadata Folders. SAS Enterprise Miner 6.1 users create projects in a specific folder location.
The default location for new SAS Enterprise Miner 6.1 projects is My Folder. The My Folder location is unique for every user and is a private location. When a SAS Enterprise Miner 6.1 user creates a project, the user can accept the default project location, or specify a different folder of their own preference. For example, a user or group of users might store mining projects in a common folder where the projects can be shared.
SAS Enterprise Miner 6.1 users will open projects by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
When the SAS Metadata Server is upgraded from SAS 9.1.3 to SAS 9.2, existing SAS Enterprise Miner 5.3 project information that was stored in the SAS Metadata Server is migrated to the Shared Data folder.
SAS administrators can view SAS Enterprise 6.1 project information via the SAS Management Console.
Models
SAS Enterprise Miner 6.1 models are stored and managed in the SAS Metadata Folders. SAS Enterprise Miner 6.1 users register models to a specific folder location.
SAS Enterprise Miner 6.1 users may now open or import models by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
When the SAS Metadata Server is upgraded from SAS 9.1.3 to SAS 9.2, existing SAS Enterprise Miner 5.3 models that were stored in the SAS Metadata Server are migrated to the Shared Data folder.
SAS administrators can view SAS Enterprise 6.1 model information via the SAS Management Console.
SAS Management Console Plug-in
The SAS Enterprise Miner 6.1 Plug-in for the SAS Management Console is revised for SAS 9.2, but maintains the same range of functionality as in SAS 9.1.3. For more information, see the SAS Enterprise 6.1 Reference Help chapters on Installation and Configuration for more information.
SAS administrators can use the SAS Management Console to view SAS Enterprise Miner project information.
Java Versions
SAS administrators retain the ability to deliver SAS Enterprise Miner 6.1 to users via Java Web Start. Java Web Start users should have Java 1.5.12 or a compatible version.
Installed versions of SAS 9.2 include Java 1.5.12. No further version of Java is required.
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Usability
SAS Enterprise Miner 6.1 provides the following improvements in usability:
Summary Statistics in Variable List Tables
The variable list tables that SAS Enterprise Miner users are familiar with have been improved in SAS Enterprise Miner 6.1. The variable view tables that surface in locations throughout the software now provide users with summary statistics for the table variables.
The summary statistics are computed by the Advanced Advisor function in the Data Source Wizard, by the Input Data node, and by the Stat Explore node. Variable summary statistics are often used to make decisions about how to treat variables in data mining models.
Configurable Attributes in Variable List Tables
SAS Enterprise Miner 6.1 is capable of displaying many different variable attribute columns in SAS Enterprise Miner variable list tables. Instead of displaying enormous tables that have many variable attribute columns, SAS Enterprise Miner 6.1 enables users to configure variable list table displays by selecting only the variable attributes that are important to their work.
Quick Text Search for SAS Code Editors and Text Viewers
The SAS Code editors and text viewers have been enhanced with a quick text search toolbar that highlights and navigates between selected text search results. This is a great aid when searching for text in SAS Code, the SAS Log, and SAS Output listings.
You can launch Quick Text Search from the SAS Enterprise Miner 6.1 main menu, or use to access the new tool bar.
Interactive Graphics Samples
Previous versions of SAS Enterprise Miner provided interactive exploratory graphics that used a quick sample of the values in a variable list table. In SAS Enterprise Miner 6.1, the quick table sample that the software performs to generate interactive graphics has been improved.
The new quick sample method scans only the attribute columns that the user selects, plus any additional Target, ID, Frequency, or Cost variables. This capability reduces the number of columns needed to perform interactive graphic sampling and increases the number of rows of data that are available for graphics.
Variable table list sampling for interactive graphics can now be performed by using a sampling algorithm that is stratified by categorical target variables. This change improves the representation of the sample in the presence of skewed data.
Project Start and Stop Code
The Project Start Code Editor window is modified to include the SAS log. Convenient access to the SAS log helps users who need to debug or modify their SAS Enterprise Miner project start code.
The Project End Code Editor window has been eliminated.
SAS Library Explorer
The SAS Library Explorer has been enhanced to view and edit (when appropriate) catalog entries of the types SOURCE, LOG, OUTPUT, and XML.
Model Import and Export
SAS Enterprise Miner 6.1 users can register models directly to the SAS Metadata Folders tree structure. This feature provides users with more control over the security, access privileges, and organization of models.
SAS Enterprise Miner 6.1 users can import a registered model into an existing data mining process flow diagram by using the Model Import node. The score code of the imported model is applied to the data in the process flow diagram, generating new model assessment statistics.
The Model Repository window has been removed from SAS Enterprise Miner 6.1. The former flat list of registered models has been replaced by a hierarchical view of models in the SAS Metadata Folders. The Model Import node provides SAS Enterprise Miner 6.1 users with a list of available models.
SAS Enterprise Miner 6.1 users can select File Open Model from the main menu to open a file utility window to browse the SAS Metadata Folders tree structure and choose a model for inspection.
SAS Enterprise Miner 6.1 users can also use the Model Import tool to navigate the SAS Metadata Folders tree structure and choose a model for addition to the process flow diagram.
Interactive Decision Tree
A switch-targets feature has been added to SAS Enterprise Miner 6.1 so that users can select a new dependent variable in a tree leaf and make new splits based on the new target. This is a powerful analytical feature for users who design decision trees for segmentation strategies.
The Interactive Decision Tree is fully integrated into SAS Enterprise Miner 6.1 and requires no separate installation or documentation.
SAS Enterprise Miner 6.1 gives users who start the software using Java Web Start users full use of the Interactive Decision Tree.
The former Tree Desktop Application that was associated with prior releases of SAS Enterprise Miner is not distributed with SAS Enterprise Miner 6.1, but is available on the SAS downloads Web page for legacy purposes.
The Tree Desktop Application will not work with a SAS 9.2 server.
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New Nodes
SAS Enterprise Miner 6.1 includes two new data mining nodes. The new nodes are presented using the SEMMA functional groupings of Enterprise Miner.
Sample — SAS Enterprise Miner 6.1 adds the following new node to the Sample tab of the Enterprise Miner tool bar:
File Import node — The File Import node enables users to directly integrate external data files into SAS Enterprise Miner 6.1 process flow diagrams. The external file types supported include dBase .DBF files, Stata .DTA files; Microsoft Excel .XLS files; SAS .JMP files; Paradox .DB files; SPSS .SAV files; Lotus .WK1, .WK3, and .WK4 files; as well as tab-delimited .TXT files; comma-delimited .CSV files; and user-defined delimited .DLM files. Data files to be imported must be located either on the SAS Enterprise Miner client machine or in a network location that is accessible to the SAS Enterprise Miner server or the SAS server system.
Model — SAS Enterprise Miner 6.1 adds the following new node to the Model tab of the Enterprise Miner tool bar:
LARS — The LARS node uses Least Angle Regression and LASSO algorithms from the SAS/STAT procedure GLMSELECT to perform model fitting tasks and sophisticated variable selection for interval target models.
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Enhanced Nodes
The following nodes in SAS Enterprise Miner 6.1 were enhanced in functionality or reorganized into new Enterprise Miner tool groups. The enhanced and changed nodes are presented using the SEMMA functional groupings of Enterprise Miner.
Sample — The following changes have been made to the Sample tools in Enterprise Miner 6.1:
Append node — The Append node enables you to concatenate two data sets together. In SAS Enterprise Miner 6.1, the Append node is able to combine training, validation, and test data sets into a single training data set for the purpose of computing full data statistics.
Explore — The following changes have been made to the Explore tools in Enterprise Miner 6.1:
Association node — The Association node is used to identify frequently occuring association and sequence patterns in transactional data. In SAS Enterprise Miner 6.1, the Association node improves by using a new SAS data mining procedure called MBSCORE. MBSCORE produces faster and more accurate output than previous versions of the Association node.
Stat Explore node — The Stat Explore node is used to generate summary statistics for data exploration. In SAS Enterprise Miner 6.1, the Stat Explore node computes summary statistics on validation and test data as well as the train data. Most Stat Explore results plots have been updated to show validation and test results. Stat Explore provides new plots that can compare variable distributions across multiple categorical targets and by-group segments.
Graph Explore node — The Graph Explore node is an advanced visualization tool for interactive data exploration. In SAS Enterprise Miner 6.1, the Graph Explore node can generate samples that are stratified by categorical target variables.
Modify — The following changes have been made to the Modify tools in Enterprise Miner 6.1:
Drop node — The Drop node is used to remove variables from metadata, SAS tables, and SAS views. In SAS Enterprise Miner 6.1, the Drop node works on data sources other than train tables. For example, in SAS Enterprise Miner 6.1, the Drop node can be used on transaction tables.
Model — The following changes have been made to the Model node tools in Enterprise Miner 6.1:
AutoNeural node — The AutoNeural node is used to automatically search for a Neural Network topology. The SAS Enterprise Miner 6.1 AutoNeural node adds a Target Layer Error Function property that permits a wider variety of distributions to be fitted. The AutoNeural node also adds a new final training phase that further refines the model after the topology has been selected.
Decision Tree node — The Decision Tree node builds statistical decision trees for predictive modeling. The SAS Enterprise Miner 6.1 Decision Tree node contains a new integrated interactive Decision Tree model building utility. Multiple target variables are supported for Interactive Decision Tree designs. Only one target is be used for model assessment statistic calculations. You can also use a Model Import node to select a different target variable and to generate model assessment statistics. Lastly, the default value for the SAS Enterprise Miner 6.1 Decision Tree sample sizes has been changed to 20,000.
Model Assessment Statistics — The model assessment statistics modules in SAS Enterprise Miner modeling nodes and in the model comparison node compute rank order statistics such as lift, captured response, and ROC. In SAS Enterprise Miner 6.1, a new algorithm provides faster and more accurate model assessment results. Some users might observe minor differences in the model assessment measurements when the analyzed data contains large proportions of observations that have tied probabilities. See the SAS Enterprise Miner Reference Help chapter on the Model Comparison node for more information about model assessment statistics.
Model Import node — The Model Import node imports registered models and models that were not created using SAS Enterprise Miner into the SAS Enterprise Miner 6.1 environment. The score code of the saved model is applied to the data that is used in the process flow diagram and new model assessment statistics are generated.
You can use the Model Import node to compare registered models to newly developed models, or to apply registered model score code to new data sets. The Model Import node and the File Import node can be used together to enable users to compare models across different projects and data sources.
Neural Network node — The Neural Network node creates feed forward networks for predictive models. The SAS Enterprise Miner 6.1 Neural Network node contains a new Weight Decay property that has an initial value of 0.0. Non-zero values for the Weight Decay property will penalize the growth of weights in the neural network, and sometimes they are used to limit overfitting in the absence of validation data. The Neural Network node Properties Panel has also been reorganized for improved usability.
Rule Induction node — The Rule Induction node builds predictive models based on incrementally identifying true cases in the data. In SAS Enterprise Miner 6.1, the default maximum number of target levels to be modeled in the Rule Induction node is increased from 32 to 1024. The increase in the maximum number of target levels facilitates the modeling of problems with high cardinality.
Assess — The following changes have been made to the Assessment node tools in Enterprise Miner 6.1:
Model Comparison node — The Model Comparison node generates comparative statistics and then automatically or manually selects a champion model from the contender models. In SAS Enterprise Miner 6.1, the Model Comparison node can compute or recompute statistics for train, validation, and test data sets. This capability is useful when model data has been modified and new model fit statistics are needed. Use the Model Comparison node together with the Append node to partition training data in order to perform model selection, and then recombine the data and compute fit statistics for the full data. The full data fit statistics are useful for model comparison purposes.
Score node — The Score node aggregates score code from the process flow diagram to create a single, deployable score code object. In SAS Enterprise Miner 6.1, the Score node scans and manipulates the SAS score code that the process flow diagram generates in order to eliminate intermediate code that produces terms that are not deployed in the final model function. The internally manipulated code is called optimized score code. The Score node now creates optimized score code by default. The Score node can also output the nonoptimized score code for comparison.
For example, the Imputation node can add SAS code that creates many new variables, but a subsequent model selection step may keep only a few of the new terms. The optimized code eliminates unused terms that were created by the Imputation node.
The optimized code will have a major positive impact on scoring and deployment processes. Fewer variables will need to be saved in the score input data sets in operational systems, which can save enterprises large amounts of resources and labor.
Utility — The following changes have been made to the Utility node tools in Enterprise Miner 6.1:
Metadata node — The Metadata node modifies the variable information, or metadata, that is passed on to subsequent tools in a process flow diagram. In SAS Enterprise Miner 6.1, you can select a single source of data and metadata for each variable table role. For example, if you have a process flow diagram with three branches, you can use the Metadata node to select a training table for one branch, a validation table for another branch, and a test table for the third branch.
The Metadata node improvements also let you modify the metadata for individual variables in each table role. This function is useful when creating jobs that process many tables. Metadata node users can also merge metadata from multiple sources. Merging metadata from multiple sources is useful when aggregating the results from multiple variable selection strategies.
For example, consider the task of combining the results of terms that were selected by a stepwise selection algorithm and a decision tree algorithm. You can retain terms that were selected by a single model, terms that were selected by a majority of models, or terms that were selected by all models. This capability provides users with a large degree of control over model creation strategies.
Reporter node — The Reporter node generates PDF and RTF documents for archiving and reporting. In SAS Enterprise Miner 6.1, the Reporter node provides new SAS ODS (Output Delivery System) functions. The new functions create document graphs, process flow diagrams, and analytical plots that match the graphics that are displayed in the SAS Enterprise Miner user interface.
The SAS Enterprise Miner 6.1 Reporter node also provides new Decision Tree results plots for use in PDF and RTF documents. In Reporter node output, the properties list for each node tool indicates the property settings that have been changed from their default values. The Reporter results window now contains a standard external file viewer that you can use to view the PDF or RTF document that was produced.
Credit Scoring — The following changes have been made to the add-on Credit Scoring node tools of Enterprise Miner 6.1:
Interactive Grouping node — The Interactive Grouping node creates and manages the grouping of raw values into modeling terms. In SAS Enterprise Miner 6.1, the Interactive Grouping node provides improved support for special code mappings; treats interval variables that have limited numbers of values as interval variables rather than categorical variables; and adds new properties that control the binning method and the number of fine detail bins.
Scorecard node — The Scorecard node builds predictive models from scorecard functions. In SAS Enterprise Miner 6.1, the Scorecard node contains several new configurable properties. The new Model Ordering property specifies the order of terms that were entered into the regression equation model selection search. New Stay, Stop, and Force properties have been added to enhance the model selection search.
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Extension Tool Programming
In Enterprise Miner 6.1, the Extension Tool Programming interface has been updated and significantly enhanced. For more information about the SAS Enterprise Miner 6.1 Extension Tool Programming Guide, see the product documentation page for SAS Enterprise Miner at http://support.sas.com.
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Copyright © 2009 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
最新的SAS企业矿工6.1
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概览
SAS企业矿工6.1是主要的开采使用的工具与新的数据发布的SAS 9.2。在改善的范围包括了许多分析和部署功能增强，以及所做整合企业Miner工具的SAS 9.2的系统设置改变。
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平台的SAS 9.2
在SAS 9.2系统是一种用于管理和部署平台的分析和改进为单用户的应用和多用户企业商业智能应用。 SAS企业矿工6.1包含了有关的SAS 9.2系统，改善矿工的SAS企业安装，安全性变更和管理。
软件版本和迁移
SAS企业矿工6.1要求的SAS 9.2平台版本。
SAS企业矿工5.3将无法运行使用SAS 9.2。
如果您现有的SAS企业矿工5.3项目储存在你的的SAS元数据，项目信息将在9.1.3格式的SAS到SAS 9.2格式在转换的SAS 9.2服务器/ SAS企业矿工6.1安装。
如果您现有的SAS企业矿工5.3项目上的数据的SAS工作区服务器，存储数据文件夹的项目不需要使用与SAS 9.2和SAS企业矿工6.1转换文件夹。所有矿工5.3 SAS企业项目数据文件夹，文件，表，视图，并基于服务器上存储的SAS工作区目录兼容使用与SAS 9.2和6.1 SAS企业矿工。
SAS企业矿工6.1用户可以打开，无需任何手动转换过程中存在的SAS企业矿工5.3项目。
SAS企业矿工6.1项目不能转换为使用SAS企业矿工5.3。
SAS企业矿工4.3用户谁希望升级使用SAS企业矿工6.1项目数据可以使用SAS企业矿工项目转换宏。该项目的升级转化宏观矿工4.3 SAS企业项目结构的SAS企业矿工5.3项目结构。 SAS企业矿工6.1开篇SAS企业矿工项目转换宏矿工5.3 SAS企业项目结构。
项目
SAS企业矿工6.1项目信息现在存储和管理的SAS元数据文件夹。 SAS企业矿工6.1用户创建在一个特定的文件夹位置的项目。
对新的SAS企业矿工6.1项目的默认位置是我的文件夹。我的文件夹的位置是独一无二的每个用户，是一个私人的位置。当矿工6.1 SAS企业用户创建一个项目，用户可以接受默认的项目位置，或指定一个他们自己的选择不同的文件夹。例如，一个用户或用户组可以存储在一个公共文件夹开采项目，其项目可以共享。
SAS企业矿工6.1用户将通过使用开放标准的打开文件窗口，显示的SAS元数据文件夹，默认情况下的树结构的项目。
当元数据服务器的SAS北欧航空公司9.1.3升级到SAS 9.2，现有的SAS企业矿工5.3项目信息，是我们在元数据服务器的SAS存储迁移到共享数据文件夹。
管理员可以查看的SAS通过管理控制台的SAS的SAS 6.1企业项目信息。
模型
SAS企业矿工6.1模型存储和管理的SAS元数据文件夹。 SAS企业矿工6.1用户注册模式，以一个特定的文件夹位置。
SAS Enterprise Miner 6.1 users may now open or import models by using a standard Open File window that displays the SAS Metadata Folders tree structure by default.
当元数据服务器的SAS北欧航空公司9.1.3升级到SAS 9.2，现有的SAS企业矿工在5.3元数据服务器的SAS存储模型迁移到共享数据文件夹。
管理员可以查看的SAS的SAS通过SAS企业级管理控制台6.1模型的信息。
的SAS管理控制台插件
SAS企业矿工为6.1插件的SAS管理控制台，是订正的SAS 9.2，而且保持了相同的功能在范围的SAS 9.1.3。有关更多信息，请参阅更多信息，SAS企业6.1安装和配置参考帮助章节。
管理员可以使用的SAS北欧航空公司管理控制台查看SAS企业矿工项目信息。
Java版本
管理员保留的SAS能够提供通过Java Web Start SAS企业矿工6.1给用户。 Java Web Start的用户都应该具有的Java 1.5.12或兼容的版本。
的SAS 9.2安装的版本，包括Java 1.5.12。没有进一步的Java版本是必需的。
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可用性
SAS企业矿工6.1可用性提供了以下改进：
概要统计变量名单表
在变量列表表SAS企业用户与矿工已在6.1 SAS企业改善矿工熟悉。鉴于该变量表表面的地点在整个软件现在提供的表变量汇总统计用户。
的汇总统计，计算由高级顾问函数在数据源向导，在输入数据节点，由统计探索节点。可变汇总统计经常被用来就如何对待数据挖掘模型变量的决定。
在可变名单表可配置属性
SAS企业矿工6.1能够显示在SAS企业矿工变量表列出许多不同的变量属性列。而不是显示有许多变量属性列巨大的表，SAS企业矿工6.1使用户能够设定变量列表表显示只选择那些他们工作的重要变量属性。
快速全文检索的SAS代码编辑器和文本观众
SAS的代码编辑器和文本观众都配备了快速的文本搜索工具，突出与所选的文本搜索结果中导航。这是一个伟大的援助文本搜索时，在SAS代码，SAS的日志，和SAS输出列表。
您可以从SAS企业矿工6.1主菜单，或使用可以进入新的工具栏的快速全文检索。
交互式图形样品
矿工的SAS企业提供互动的早期版本中所使用表变量列表的值快速样本探索图形。在SAS企业矿工6.1，快捷的表样，该软件执行产生互动图形已有所改善。
新的快速抽样方法只扫描属性列加任何额外的目标，身份证，频率，或成本变量，用户选择。该功能减少了所需的采样进行图形交互列数，增加了数据行数图形可用。
变量表列出交互式图形抽样现在可以通过使用采样算法，通过明确目标变量分层。此更改提高了中存在的扭曲的数据样本的代表性。
项目启动和停止码
该项目启动代码编辑器窗口的修改，以包括的SAS日志。方便地帮助用户的SAS日志谁需要调试或修改其SAS企业矿工项目启动代码。
在项目结束代码编辑器窗口已被消除。
图书馆资源管理器的SAS
SAS的图书馆资源管理器已得到增强，查看和编辑（在适当的时候）的类型目录条目的来源，日志，输出，和XML。
模型导入和导出
SAS企业矿工6.1用户可直接向登记模式的SAS元数据文件夹的树状结构。此功能提供了更多对用户的安全控制，访问权限，以及模型的组织。
SAS企业矿工6.1用户可以导入到现有的数据挖掘过程流程图通过模型导入节点注册的模特儿。在进口模型评分代码应用到工艺流程图中的数据，产生新的模式评估统计。
示范库窗口已被删除从SAS企业矿工6.1。前者单位的注册最多的车型名单已取代在文件夹的SAS元数据模型的分层视图。该模型导入节点提供SAS 6.1企业矿工的可用型号的用户。
SAS企业矿工6.1用户可以选择从主菜单文件打开模式打开文件浏览窗口工具的SAS元数据文件夹树结构，然后选择一个检查模式。
SAS企业矿工6.1用户还可以使用模型导入工具导航的SAS元数据文件夹树状结构，并选择了除工艺流程图模型。
互动决策树
阿开关的目标功能已被添加到SAS企业矿工6.1，使用户可以选择新的叶子在树上因变量，并就新的目标为基础的新的分裂。这是一个功能强大的分析功能，为用户谁设计的细分策略决策树。
互动决策树是完全集成到SAS企业矿工6.1，无需单独安装或文档。
SAS企业矿工6.1为用户提供了谁启动软件使用Java Web Start用户的互动，充分利用决策树。
前树桌面应用程序，是符合SAS企业矿工以前的版本是不相关的分布与SAS 6.1企业矿工，但基于SAS可供下载的Web页面遗产的目的。
树桌面应用程序将无法工作与SAS 9.2服务器。
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新节点
SAS企业矿工6.1包括两种新的数据挖掘的节点。新的节点提出利用企业集团的矿工SEMMA功能。
样品- SAS企业矿工6.1添加了以下新的节点企业的矿工工具栏样本标签：
文件导入节点-该文件导入节点使用户可以直接集成到SAS企业矿工外部数据文件6.1流程图。外部支持的文件类型包括的dBASE。DBF文件而言，Stata。差热分析的文件; Microsoft Excel中。XLS文件，SAS等。选配计划的文件;悖论。DB文件，酵素。SAV文件，莲花。周价格。WK3，和。WK4文件;为以及制表符分隔。TXT文件，逗号分隔的。CSV文件，和用户定义的分隔。DLM文件。数据文件输入必须是基于SAS企业矿工的客户机或网络中的位置，都可以访问企业矿工的SAS服务器或SAS服务器系统的位置。
模型- SAS企业矿工6.1添加了以下新的节点企业的矿工工具栏型号标签：
拉尔斯-拉尔斯节点使用的最角回归和从SAS拉索算法/转录过程GLMSELECT模型拟合来执行任务和复杂的间隔目标模型变量选择。
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增强节点
SAS企业级矿工在6.1以下节点的功能得到了加强，或到新的企业Miner工具集团重组。增强和改变节点提出了利用企业集团的矿工SEMMA功能。
示例-下面的更改已作出示例工具企业矿工6.1：
附加节点-追加节点，您可以连接两个数据集在一起。在SAS企业矿工6.1，追加节点能够结合训练，验证，并在单一培训的完整数据计算统计目的的一组数据测试数据集。
探索-以下修改过矿工6.1在企业的探索工具：
协会节点-协会节点是用来识别和频繁发生的关联交易中的数据序列模式。在SAS企业矿工6.1，该协会节点提高了使用新的SAS数据挖掘过程调用MBSCORE。 MBSCORE生产更快和更精确的输出比以前的版本协会节点。
统计探索节点-探索的统计节点用于生成汇总统计数据的探索。在SAS企业矿工6.1统计探索节点计算的验证和测试数据的汇总统计以及列车的数据。大多数统计探索的结果曲线已经经过更新以显示验证和测试结果。统计探索提供了新的阴谋，可以比较多个和明确的目标变量分布的组部分。
图探索节点-探索节点的图是一个先进的勘探交互式数据可视化工具。在SAS企业矿工6.1格拉夫探索节点可以生成样本，由分层明确目标变量。
修改-下列变更已在企业矿工6.1修改工具：
下降节点-在下拉节点用于去除数据变量的SAS表，和SAS的意见。在SAS企业矿工6.1拖放节点工程的数据源表比其他列车。例如，在SAS企业矿工6.1拖放节点可用于交易表。
模型-下面的更改已作出示范节点工具，在企业矿工6.1：
AutoNeural节点- AutoNeural节点用于自动寻找一个神经网络的拓扑结构。 SAS企业矿工6.1 AutoNeural节点添加了一个目标层误差函数的财产，允许更多的发行各种被套。该AutoNeural节点还增加了一个新的最后训练阶段，进一步细化后的拓扑结构已选定的模式。
决策树节点-决策树节点建立预测模型的统计决策树。 SAS企业矿工6.1决策树节点包含一个新的综合互动决策树模型的建立实用工具。多目标变量支持互动决策树设计。只有一个目标，可用于评估的统计模型计算。您也可以使用一个模型导入节点选择不同的目标变量，生成模式评估统计。最后，对矿工的SAS 6.1企业抽样规模决策树的默认值已更改为20000。
模型评估统计-统计模型评估模块的SAS企业矿工建模节点和节点的计算模型的比较，如电梯次第统计，被俘的反应，和中华民国。在矿工6.1 SAS企业，一个新的算法提供更快，更精确的模型评估的结果。有些用户可能会观察该模型评估测量小异的分析数据时，包含有密切联系的概率较大比例的意见。见SAS企业级示范比较有关模型评估统计信息节点矿工参考帮助篇章。
模型导入节点-节点的模型导入进口注册的模式，并没有把创建的SAS企业级矿工6.1环境SAS企业矿工模型。在保存的模型评分代码适用于所使用的程序流程图及评估的新模式产生的数据统计。
您可以使用节点的模型导入注册模式比较新发展模式，或申请注册的模特儿评分代码，新的数据集。该模型导入节点和文件导入节点可以一起使用，使用户能够比较不同的项目和数据源模型。
神经网络节点-神经网络节点的创造的前馈网络的预测模型。 SAS企业矿工6.1神经网络节点包含一个新的重量衰减属性，有一个初始值为0.0。非零重量衰减属性值会惩罚权重的神经网络的发展，有时它们被用来限制在验证数据的情况下过拟合。神经网络节点的属性面板也已改组，以提高可用性。
规则归纳节点-节点的规则归纳的基础上逐步确定了数据真实个案为基础的预测模型。在SAS企业矿工6.1的目标水平默认最大数量的规则归纳节点模型从32增加至1024。在目标水平的最大数量的增加促进了高基数问题建模。
评估-下列变更已在企业矿工6.1节点的评估工具：
型号比较节点-节点生成模型的比较比较统计数字，然后自动或手动选择从竞争者模型冠军模型。在SAS企业矿工6.1型号比较节点可以计算列车或重新计算，验证统计数据和测试数据集。这种能力是非常有用的模型数据已被修改，新的模型拟合统计量是必要的。使用该模型的比较节点与节点追加分区训练数据，以执行模式的选择，然后重组的数据和计算的全部数据拟合统计。完整的数据拟合统计为模型进行比较有用。
分数节点-节点的分数汇总评分从程序流程图的代码创建一个单一的，可部署的评分代码的对象。在SAS企业矿工6.1分数节点扫描和操纵SAS评分代码的程序流程图生成，以消除产生的中间代码是不会在最后模型函数部署条件。国内操纵的代码被称为优化评分代码。现在的分数节点优化创建默认评分代码。节点的分数也可以输出比较nonoptimized评分代码。
例如，归责节点可以增加SAS代码创建了许多新的变数，但随后的模型选择步骤可能只保留了一些新的条款。的优化代码消除的是由未使用的归责节点创建条件。
优化的代码对得分和部署过程重大，积极的影响。较少的变量将需要在分数输入数据业务系统，可以节省企业的资源和劳动力大量套保存。
实用-下面的更改已作出的实用工具，在企业节点矿工6.1：
元数据节点-元数据节点的修改变量信息，或元数据，即通过在工序流程图随后的工具。在SAS企业矿工6.1，你可以选择一个数据和每个变量表的作用元数据的单一来源。例如，如果您有三个部门的工艺流程图，您可以使用元数据节点选择一个分支，在另一分行验证表，第三个分支一个测试表的训练表。
元数据节点的改进也让您修改每个表中的作用个体变量元数据。此功能时非常有用创造就业机会的过程中的许多表。元数据节点用户还可以合并来自多个源的数据。合并来自多个源的数据时非常有用来自多个变量选择策略的结果。
例如，考虑相结合的，分别由一个逐步的选择算法和决策树算法的选择方面成果的任务。你可以保留，分别由一个单一的模式，即是由大多数的模型，或者是由所有型号选择条件选择条件选择条款。此功能提供了一种控制模型的创建策略很大程度上用户。
记者节点-记者节点生成PDF格式和存档和通报RTF文档。在SAS企业矿工6.1记者节点提供新的SAS消耗臭氧层物质（输出传送系统）功能。新的函数创建图形文件，工艺流程图，并分析阴谋，匹配的是SAS企业矿工用户界面中显示的图形。
SAS企业矿工6.1记者节点还提供了PDF和RTF文件，使用新的决策树结果阴谋。在记者节点的输出，每个节点的工具属性列表显示的财产已经从它们的默认值更改的设置。记者结果窗口现在包含一个标准的外部文件浏览器，您可以使用浏览PDF或RTF文档制作。
信用评分-以下变化作了一些附加的企业信用评估矿工6.1节点工具：
互动分组节点-互动分组节点创建和管理纳入模型计算的原始值分组。在SAS企业矿工6.1互动分组节点提供了改进的特殊代码映射支持，给予该有，而不是绝对的变量区间变量的值数量有限区间变量，并增加了新的属性，控制分块方法和一些细节垃圾箱。
记分卡节点-节点生成的记分卡的记分卡的功能预测模型。在SAS企业矿工6.1记分卡节点包含几个新的配置属性。新示范订购属性指定的条款顺序分为回归方程模型选择搜索输入。新的住宿，停止和部队属性已被添加到提高模型选择搜索。
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扩展编程工具
在企业矿工6.1，扩展工具编程接口已更新，显着提高。如需有关SAS企业矿工6.1扩展工具编程指南信息，请参阅SAS企业矿工在http://support.sas.com产品文档页面。
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