data mining - association analysis.pdf

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Data Mining: Association Analysis

Applies to:SAP BI 7.0. For more information, visit the EDW homepage

Summary

This article deals with Data Mining and it explains the classification method „Association Analysis‟ in detail. Italso explains the steps for implementation of Association by creating a Model and an Analysis Process.

Author: Vishall Pradeep K.S

Company: Applexus Technologies (P) Ltd

Created on: 5 May 2011

Author Bio

Vishall Pradeep is working as SAP Technology Consultant with Applexus Technologies (P) Ltd. He hasexperience in SAP ABAP and SAP BI

http://www.sdn.sap.com/irj/sdn/edw








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Table of Contents

Introduction ......................................................................................................................................................... 3

Association Analysis ....................................................................................................................................... 3

Creating a Model ............................................................................................................................................. 3

Creating a Analysis Process for Training ........................................................................................................ 6

Maintaining DataSource for Association Rules ............................................................................................. 13

Related Content ................................................................................................................................................ 15

Disclaimer and Liability Notice .......................................................................................................................... 16





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Introduction

Data mining is to automatically determine significant patterns and hidden associations from large amounts ofdata. Data mining provides you with insights and correlations that had formerly gone unrecognized or beenignored because it had not been considered possible to analyze them. The data mining methods available inSAP BW allow you to create models according to your requirements and then use these models to drawinformation from your SAP BW data to assist your decision-making.

Association Analysis Association analysis uncovers hidden patterns, correlations or casual structures among a set of items orobjects. For example, association analysis enables you to understand what products and services customerstend to purchase at the same time. By analyzing the purchasing trends of your customers with associationanalysis, you can predict their future behavior. The purpose of association analysis is to find patterns inparticular in business processes and to formulate suitable rules. Association analysis determines these rulesby using historic data to train the model. You can display and export the determined association rules.

Creating a Model

Go to Transaction RSDMWB (Data Mining Workbench)

Data Mining->Expand Association Analysis->Right Click Association Analysis->Create Model





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Choose the Model Name and Description

The method name for which you are creating a model is displayed. You have three options for modelfield selection

To create the model fields manually, select the Manual option.

If you want to create a model that is similar to an existing model created previously, you can copy itchoosing the Use Model as Template option. You can make minor changes to the copied versionmanually to suit your requirements

To create a model from a query, choose Model Field Selection and select the query which you wantuse as a source for model fields .The InfoObjects contained in the selected query are available asmodel fields





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The screen shows the list of Fields and we can select and exclude fields in it

In the Fields tab, to specify which characteristic is to be considered with which attributes and fieldparameters are used to specify weightings for the individual attributes. The system then establishesformerly unknown associations between the attribute values





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Model Fields tab is used to specify which transactions and which items should be considered

Model Parameters tab is used to specify what percentage of the transactions with the leading itemshould also contain the dependent item to define a valid rule (confidence). Coupled with this, you canuse the parameters Lift and Support to improve the quality of the determined rules. Moreover, youcan specify the number of leading and dependent items

Support -> Percentage of all the transactions that contain the item set.

Confidence ->Percentage of the transactions containing the leading items that also contain thedepending items

Lift -> Confidence divided by support of the depending product and Lift helps to identify and eliminate

rules that are only generated because some of the items naturally occur very frequently, althoughthere is no actual association between the set of leading and depending items

Save and Activate the Model (we can only train or valuate a model or use it for the prediction if themodel has been activated.)

Creating a Analysis Process for Training

We can create an analysis process for a data mining method to train a data mining model. Thepurpose of training a model using historic data is to allow the model to learn from the historic data.The training result can then be used for a prediction or in the operational system

Go to Transaction RSANWB (Analysis Process Designer)

http://help.sap.com/saphelp_erp2004/helpdata/en/bc/22ece86577d411b1360060b03c6bfb/content.htm

http://help.sap.com/saphelp_erp2004/helpdata/en/1e/37145893d67440b8bb3342aed09d65/content.htm

http://help.sap.com/saphelp_erp2004/helpdata/en/11/83f7d91b77d411b1360060b03c6bfb/content.htm

http://help.sap.com/saphelp_erp2004/helpdata/en/11/83f7d91b77d411b1360060b03c6bfb/content.htm

http://help.sap.com/saphelp_erp2004/helpdata/en/1e/37145893d67440b8bb3342aed09d65/content.htm

http://help.sap.com/saphelp_erp2004/helpdata/en/bc/22ece86577d411b1360060b03c6bfb/content.htm





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Choose General->Right Click->Create

Give the description to the APD

From the Data Sources, drag and drop the Query to the work area





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It asks for a Popup and click on Choose Query

From the Help, Select the query

And Click “OK”





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The Query which is the data Source is added as below

For the data target, drag the icon for the relevant data mining method in the work area

Double click on data mining node to make the settings in the dialog box that appears Choose the required model from F4 Help





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Click on “ENTER” and Connect the two nodes

To make an explicit field assignment, double click on the data flow arrow that connects the nodes

Click on Automatic Assignment and choose Same Infoobject





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Click on Continue and Save and activate the APD

While saving it will ask for a Technical Name

Execute the APD

The data is written to the data target and a log is displayed

To view the training results, in the context menu of data target, choose Data Mining Model ViewModel Results





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It will ask for a Popup and we can restrict values according to leading and depending items andchoose “Execute”.

The Results will be shown as below





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Defined in Package->User defined dates during extraction in InfoPackage and we must define thestart and end dates in the staging process as part of InfoPackage maintenance. These dates aretaken as the valid dates for the extracted data.

Fixed Time Interval->Fixed dates and we must specify the start and end dates while maintaining theDataSource. The default value for the start date is the date on which the datsource is created. Thedefault value for end date is the maximum date, that is, 31.12.9999

Others->We can either enter Date of Extraction or Date of Analysis and Date of analysis is either thetraining date (for the DataSource based on the training source) or prediction date (for theDataSource based on the prediction source)

Choose the Option Required and Click on “Create” It displays the details of the associate DataSource as below

Click on Save

A DataSource is Maintained for the created model





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Related Content

Data Mining: Decision Trees

Data Mining: Clustering

http://forums.sdn.sap.com/thread.jspa?threadID=1186413

For more information, visit the EDW homepage

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Disclaimer and Liability Notice

This document may discuss sample coding or other information that does not include SAP official interfaces and therefore is notsupported by SAP. Changes made based on this information are not supported and can be overwritten during an upgrade.SAP will not be held liable for any damages caused by using or misusing the information, code or methods suggested in this document,and anyone using these methods does so at his/her own risk.

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data mining - association analysis.pdf

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