How To Register A Model In Sas Miner And Use In Guide

How SAS Enterprise Miner simplifies the data mining process

The SAS Enterprise Miner data mining tool helps users develop descriptive and predictive models, including components for predictive modeling and in-database scoring.

SAS Enterprise Miner is an avant-garde analytics data mining tool intended to help users apace develop descriptive and predictive models through a streamlined data mining process.

Enterprise Miner's graphical interface enables users to logically move through the 5-step SAS SEMMA approach: sampling, exploration, modification, modeling and assessment. Users tin build a process flow by selecting the appropriate tab from Enterprise Miner's toolbar, and so dragging and dropping step-specific nodes onto a pallet.

Enterprise Miner supports several algorithms and techniques, including determination copse, time serial, neural networks, linear and logistic regression, sequence and web path analysis, market place handbasket analysis, and link analysis.

Enterprise Miner's client-server compages enables business concern users and data analysts to collaborate and share models and other work. Client software operates on Microsoft Windows seven, 8 and 10. Server host options include the following:

HP-UX on Itanium 11i version 3 (11.31);
IBM AIX R64 on Power architecture 7.1;
IBM z/OS V1R12 and higher;
Linux x64 (64-bit), including SUSE Enterprise 11 SP1, Red Chapeau Enterprise Linux 6.1 and 6.vii, and Oracle Linux 6.1;
Microsoft Windows on x64 (64-flake), including desktop Windows 7 x64 SP1, Windows 8 x64, and Windows ten x64 or Server -- Windows Server 2008 x64 SP2 family, Windows Server 2008 R2 SP1 family, Windows Server 2012 family;
Solaris on Sparc version x, update 9; and
Solaris on x64 (x64-x86): version ten, update nine; version 11.

Enterprise Miner features for the data mining procedure

SAS Rapid Predictive Modeler is a component of SAS Enterprise Miner that tin can run every bit an add-on to Microsoft Excel, enabling business users to perform predictive modeling straight from within their Excel spreadsheets. Models developed in Rapid Predictive Modeler can be customized by data analysts using Enterprise Miner.

Integration of R code. Analysts and developers who develop in the R language can integrate the models and transformations they write within an Enterprise Miner process flow.

Support for in-database and in-Hadoop scoring. When combined with a SAS Scoring Accelerator, scoring algorithms created in SAS Enterprise Miner can be deployed and executed within a database or Hadoop surroundings. Scoring Accelerators are available for Hadoop, Pivotal, DB2, IBM Netezza, Oracle, Teradata and SAS Scalable Performance Data Server.

SAS likewise offers Mill Miner, an add-on product that provides users with an automated, web-based framework to aid them reduce the time needed to develop models. The production enables users to build, run and retrain multiple predictive models across business organisation or customer segments quickly. It tin can likewise help identify a champion model.

Release 14.2 improved upon the previous version of Enterprise Miner by adding new nodes to execute code in a SAS Viya environs -- an open up, deject-ready, in-retentiveness platform -- as part of a process flow diagram. Other enhancements include improvements to the Score node and Score Lawmaking Export nodes.

Enhancements in Factory Miner 14.two enable users to create batch code that can be used for retraining models with updated data.

Contact SAS for pricing. Although in that location is no trial version of Enterprise Miner, SAS offers members of academia complimentary use of its products through spider web access via its SAS OnDemand for Academics offer.