IBM 15 User Manual
i
IBM SPSS Modeler 15 User’s Guide
Note: Before using this information and the product it supports, read the general information
under Notices on p. 249.
This edition applies to IBM SPSS Modeler 15 and to all subsequent releases and modifications
until otherwise indicated in new editions.
Adobe product screenshot(s) reprinted with permission from Adobe Systems Incorporated.
Microsoft product screenshot(s) reprinted with permission from Microsoft Corporation.
Licensed Mate
© Copyright IBM Corporation 1994, 2012.
rials - Property of IBM
U.S. Government Users Restricted Rights - Use, duplication or disclosure restricted by GSA ADP
Schedule Contract with IBM Corp .
Preface
IBM® SPSS® Modeler is the IBM Co r p. enterprise-strength data mining workbench. SPSS
Modeler helps organizations to improve customer and citizen relat ionships th r ough an in-depth
understandi
profitable customers, identify cross-selling opportunities, attract new customers, detect f raud,
reduce risk, and improve government service delivery.
SPSS Modeler
leads to more powerful predictive models and shortens time-to-solution . SPSS Modeler offers
many modeling techniques, such as prediction, c lassification, segmentation, and association
detection a
enables t heir deliver y enterprise-wide to decision makers or to a database.
ng of data. Organizations use the insight gained from SPSS M odeler to retain
’s visual interface invites users to apply t heir specific business expertise, which
lgorithms. Once models are created, IBM® SPSS® Modeler Solution Publisher
About IBM Bu
IBM Business Analytics software delivers complete, consistent and accurate information that
decision-makers trust to improve business performance. A comprehensive portfolio of business
intelligence, predictive analytics, financial performance and strategy m anagement, and analytic
applications provides clear, immediate and actionable in sights into current performance and the
ability to predict future outcomes. Combined with rich industry solution s, proven practices and
professional services, organizations of every size can drive the highest productivity, confidently
automate decisions and deliver better results.
As part of
future events and proactively act upon that insight to drive bet ter business outcomes. Commercial,
government and academic customers worldwide rely on IBM SPSS technology as a competitive
advantag
risk. By incorporating IBM SPSS software into their daily operations, organizations become
predictive enterprises – able to direct and automate decisions to meet busin ess goals and achieve
measura
http://www.ibm.com/spss.
Techni
cal support
Technical support is available to maintenance custome r s. Customers may contact Technical
Support for assistance in using IBM Corp. products or for installation help for one of the
supported hardware environments. To reach Technical Support, see the IBM Corp. web site
at http://www.ibm.com/support. Be prepared to identify yourself, your organization, and your
support agreement when requesting assistance.
siness Analytics
this portfolio, IBM SPSS Predictive Analytics software helps organizations predict
e in attracting, retaining and growing customers, while reducing fraud and mitigating
ble competitive advantage. For further information or to reach a representative visit
© Copyright IBM Corporation 1994, 2012.
iii
Contents
1 About IBM SPSS Modeler 1
IBM SPSS Modeler Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
IBM SPSS Modeler Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
IBM SPSS Modeler Administration Console . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
IBM SPSS Modeler Batch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
IBM SPSS Modeler Solution Publisher. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
IBM SPSS Modeler Server Adapters for IBM SPSS Collaboration and Deployment Services . 2
IBM SPSS Modeler Editions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
IBM SPSS Modeler Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
SPSS Modeler Professional Documentation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
SPSS Modeler Premium Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Application Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Demos Folder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2 New Features 7
New and Changed Features in IBM SPSS Modeler 15 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
New features in IBM SPSS Modeler Professional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
New features in IBM SPSS Modeler Premium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
New Nodes in This Release . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3 IBM SPSS Modeler Overview 12
Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Starting IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Launching from the Command Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Connecting to IBM SPSS Modeler Server . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Changing the Temp Directory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Starting Multiple IBM SPSS Modeler Sessions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
IBM SPSS Modeler Interface at a Glance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
IBM SPSS Modeler Stream Canvas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Nodes Palette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
IBM SPSS Modeler Managers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
IBM SPSS Modeler Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
IBM SPSS Modeler Toolbar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Customizing the Toolbar. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Customizing the IBM SPSS Modeler Window. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
© Copyright IBM Corporation 1994, 2012.
iv
Changing the icon size for a stream . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Using the Mous
Using Shortcut Keys . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Printing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Automating IB
e in IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
M SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4 Understandin
Data Mining Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
Assessing the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
A Strategy for Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
The CRISP-DM Process Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Types of Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Data Mining Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
g Data Mining 29
5 Building Streams 41
Stream-Building Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Building Data Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Working with Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Working with Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Stream Descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Running Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Working with Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Adding Comments and Annotations to Nodes and Streams . . . . . . . . . . . . . . . . . . . . . . . . . . 78
Saving Data Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Loading Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
Mapping Data Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Tips and Shortcuts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
6 Handling Missing Values 99
Overview of Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
Handling Missing Values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
Handling Records with Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Handling Fields with Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
Imputing or Filling Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
CLEM Functions for Missing Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
v
7 Building CLEM Expressions 105
About CLEM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
CLEM Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
Values and Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110
Expressions and Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Stream, Session, and SuperNode Parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Working with Strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
Handling Blanks and Missing Values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Working with Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Working with Times and Dates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
Summarizing Multiple Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
Working with Multiple-Response Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
The Expression Builder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
Accessing the Expression Builder . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Creating Expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
Selecting Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
Selecting Fields, Parameters, and Global Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
Viewing or Selecting Values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
Checking CLEM Expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
Find and Replace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
8 CLEM Language Reference 127
CLEM Reference Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
CLEM Datatypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Integers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Reals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Characters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
Strings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Lists. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Fields. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Dates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
CLEM Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
Functions Reference. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Conventions in Function Descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
Information Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
Conversion Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
Comparison Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
vi
Logical Functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Numeric Funct
Trigonometric Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Probability Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
Bitwise Integ
Random Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
String Functions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
SoundEx Functi
Date and Time Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
Sequence Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
Global Functio
Functions Handling Blanks and Null Values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
Special Fields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
ions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
er Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
ons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
ns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
9 Using IBM SPSS Modeler with a Repository 158
About the IBM SPSS Collaboration and Deployment Services Repository . . . . . . . . . . . . . . . . . . 158
Storing and Deploying Repository Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
Connecting to the Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
Entering Credentials for the Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Browsing the Repository Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
Storing Objects in the Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Setting Object Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
Storing Streams. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
Storing Projects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
Storing Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Storing Output Objects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Storing Models and Model Palettes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Retrieving Objects from the Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
Choosing an Object to Retrieve . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Selecting an Object Version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 174
Searching for Objects in the Repository . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Modifying Repository Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Creating, Renaming, and Deleting Folders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Locking and Unlocking Repository Objects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Deleting Repository Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
Managing Properties of Repository Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Viewing Folder Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179
Viewing and Editing Object Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
Managing Object Version Labels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
vii
Deploying Streams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
Stream Deployment Options. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
The Scoring Br
anch. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
10 Exporting to E
About Exporting to External Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Opening a Stream in IBM SPSS Modeler Advantage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
Importing and Exporting Models as PMML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196
Model Types Supporting PMML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
xternal Applications 195
11 Projects and Reports 200
Introduction to Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200
CRISP-DM View. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
Classes View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Building a Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Creating a New Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
Adding to a Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
Transferring Projects to the IBM SPSS Collaboration and Deployment Services Repository . 204
Setting Project Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
Annotating a Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
Object Properties. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
Closing a Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Generating a Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Saving and Exporting Generated Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
12 Customizing IBM SPSS Modeler 215
Customizing IBM SPSS Modeler Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
Setting IBM SPSS Modeler Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
System Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215
Setting Default Directories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216
Setting User Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Setting User Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
viii
Customizing the Nodes Palette . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
Customizing the Palette Manager . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
Changing a Pal
CEMI Node Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
ette Tab View . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
13 Performance Considerations for Streams and Nodes 230
Order of Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
Node Caches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
Performance: Process Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Performance: Modeling Nodes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
Performance: CLEM Expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
Appendices
A Accessibility in IBM SPSS Modeler 236
Overview of Accessibility in IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Types of Accessibility Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Accessibility for the Visually Impaired . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
Accessibility for Blind Users . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
Keyboard Accessibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
Using a Screen Reader . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
Tips for Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
Interference with Other Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
JAWS and Java. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
Using Graphs in IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
B Unicode Support 248
Unicode Support in IBM SPSS Modeler . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
ix
C Notices 249
Index 252
x
About IBM SPSS Modeler
IBM® SPSS® Modeler is a set of data mining tools that enable you to quickly deve lop predictive
models using business expertise and deploy them into business o pe r ations to improve decision
making. Desi
entire data mining process, from data to better business results.
SPSS Modeler offers a va r iety of modeling methods taken from machine learning, art ificial
intelligence, and statistics. The methods available on the Modeling palette allow you to derive
new information from your data and to develop predictive models. Each method has certain
strengths and is best suited for particular types of problems.
SPSS Modeler can be purchased as a standalone p r oduct, or used as a client in
combination with SPSS Modeler Server. A number of additional options are also
available, as summarized in the following sections. For more information, see
http://www.ibm.com/software/analytics/spss/products/modeler/.
gned aroun d the industry-standard CRISP-DM model, SPSS Modeler supports t he
Chapter
1
1
11
IBM SPSS Modeler Products
The IBM® SPSS® Modeler family of products and associated software comprises the following.
IBM SPSS Modeler
IBM SPSS Modeler Server
IBM SPSS Modeler Administration Console
IBM SPSS Modeler Batch
IBM SPSS Modeler Solution Publisher
IBM SPSS Modeler Server adapters for I BM SPSS Collaboration and Deployment Services
IBM SPSS Modeler
SPSS Modeler is a functionally complete version of the produc t that you install and run on your
personal computer. You can run SPSS Modeler in local mode as a standalone product, or use it
in distributed mode along with IBM® SPSS® Modeler Server for im proved performance on
large data sets.
With SPSS Modeler, you can build a ccurate p r edictive models quickly and intuitively, withou t
programming. Using the un ique visual interface, you can easily visualize the data mining process.
With the support of the advanced analytics embedded in the product, you can discover previously
hidden patterns and trends in your data. You can mode l outcomes and understand the factors that
influence them, enabling you to take advantage of business opportunities and mitigate risks.
SPSS Modeler is available in two editions: SPSS Modeler Professional and SPSS Modeler
Premium. For more information, see the topic IBM SPSS Modeler Editions on p. 3.
© Copyright IBM Corporation 1994, 2012.
1
2
Chapter 1
IBM SPSS Modeler Server
SPSS Modeler uses a client/server architecture to distribute requests for resource-intensive
operations to powerful server software, resulting in faster performance on larger data sets.
SPSS Modeler Server is a separately-licensed product that runs continually in distributed analysis
mode on a server host in conjunction with one or more IBM® SPSS® Modeler installations.
In this way, SPSS Modeler Server provides superior performance on large data sets because
memory-intensive operations can be done on the server without downloading data to the client
computer. IBM® SPSS® Modeler S erver also provides support for SQL optimization and
in-database modeling capabilities, delivering further benefits in performance and automation.
IBM SPSS Modeler Administration Console
The Modeler Administration Console is a graphical application for managing many of the SPSS
Modeler Server configuration options, which are also configurable by means of an options file.
The appl ication provides a console user interface to monitor and configure your SPSS Modeler
Server installations, and is available free-of-charge to current SPSS Modeler Server customers.
The applicatio n can be installed only o n Windows computers; however, it can administer a server
installed on any supported platform.
IBM SPSS Modeler Batch
While data mining is usually an interactive process, it is also possible to run SPSS Modeler
from a command line, with out the need for the graphical user interf ace. For example, you might
have long-running or repetitive tasks that you want to perform with no user intervention. SPSS
Modeler Batch is a special ver sion of the product that provides support f or the complete analytical
capabilities of SPSS Modeler without access to t he regular user interface. An SPSS Modeler
Server license is required to use SPSS Modeler Batch.
IBM SPSS Modeler Solution Publisher
SPSS Modeler Solution Pub lisher is a tool that enables you to create a packaged version of an
SPSS Modeler stream that can be run by an external runtime engine or embedded in an external
application. In this way, you can publish and deploy complete SPSS Modeler streams for use in
environments that do not have SPSS Modeler installed. SPSS Modeler Solution Publisher is
distributed as part of the IBM SPSS Collaborat ion and Deployment Services - Scoring service,
for which a separate license is required. With this lice nse, you receive SPSS Modeler Solution
Publisher Runtime, which enables you to execute the published streams.
IBM SPSS Modeler Server Adapters for IBM SPSS Collaboration and Deployment Services
A number of adapters for IBM® SPSS® Collaboration and Deployment Services are available that
enable SPSS Modeler and SPSS Modeler Server to interact with an IBM SPSS Collaboration and
Deployment Services repo sitory. In this way, an SPSS Modeler stream deployed to the repository
can be shared by multiple users, or accessed from the thin-cl ient application IBM SPSS Modeler
Advantage. Yo
u install the adapter on the system that hosts the repository.
IBM SPSS Modeler Editions
SPSS Modeler is available in the following editions.
SPSS Modeler Professional
SPSS Modeler Professional provides all the tools you need to work with most types of structured
data, such as behaviors and interactions tracked in C RM systems, demographics, purchasing
behavior and sales data.
SPSS Modeler Premium
3
About IBM SPSS Modeler
SPSS Modeler Premium is a separately-licensed product that extends SPSS Modeler Pro f essional
to work with specialized data such as that us ed for entity analytics or social networkin g, and with
unstructured text data. SPSS Modeler Premium comprises the following components.
IBM® SPSS® Modeler Entity Analytics adds a completely new dimension to IBM® SPSS®
Modeler predictive analytics. Whereas predictive analytics attempts to predict future behavior
from pas t data, entity analytics focuses on improving the cohere nce and consistency of current
data by resolving identity conflicts within the records themselves. An identity can be that of an
individual, an organization, an object, or any other entity for whic h ambiguity might exist. Identity
resolution can be vital in a number of fields, including customer relationship management, fraud
detection, anti-money laundering, and national and international security.
IBM SPSS Modeler Social Network Analysis transforms information about relationships into
fields that characterize the social behavior of individuals and groups. Using data describing
the relati onships underlying social networ ks, IBM® SPSS® Modeler Social Network Analysis
identifies social leaders who influence the behavior of others in the network. In addition, you can
determine which people are most affected by other network participants. By combining these
results with othe r measure s, you can create comprehensive profiles of individuals on which to
base your predictive models. Models that include this social information will perform better than
models that do not.
IBM® SPSS® Modeler Text Analytics uses advanced ling uistic technologies and Natural
Language Processing (NLP) to rapidly process a large variety of unstructured text data, extract
and organize the key concepts, and group th
categories can be combined with existing structured da ta, such as demographics, and applied to
modeling using the full suite of SPSS Modeler data mining tools to yield better and more focu sed
decisions.
ese concepts into categories. Extracted concepts and
4
Chapter 1
IBM SPSS Modeler Documentation
Documentation in online help form at is available from the Help menu of SPSS Modeler. This
includes documentation for S PSS Modeler, SPSS Modeler Server, and SPSS Modeler Solution
Publisher, as well as the Applications Guide and other supporting materials.
Complete do cumentation for each product (including installation instructions) is available in PDF
format under the \Documentation folder on each product DVD. Installation documents can also be
downloaded from the web at http://www-01.ibm.com/support/docview.wss?uid=swg27023172.
Documentation in both formats is also available from the SPSS Modeler Information Center at
http://publib.boulder.ibm.com/infocenter/spssmodl/v15r0m0/.
SPSS Modeler Professional Documentation
The SPSS Modeler Professional documentation suite (excluding installation instruc tions) is
as follows.
IBM SPSS Modeler User’s Guide.
to build data streams, handle missing values, build CLEM expressions, work w ith projects and
reports, and package streams for deployment to IBM SPSS Collaboration and Deployment
Services, Predictive Applications, or IBM SPSS Modeler Advantage.
IBM SPSS Modeler Source, Process, and Output Nodes.
read, process, and o utput data in different formats. Effective ly this means all nodes other
than modeling nodes.
IBM SPSS Modeler Modeling Nodes.
models. IBM® SPSS® Modeler offers a v ariety of modeling methods taken from machine
learning, artificial intelligence, and sta tistics.
IBM SPSS Modeler Algorithms Guide.
modeling methods used in SPSS Modeler. This guide is available in P DF format only.
IBM SPSS Modeler Applications Guide.
introductions to specific modeling methods and techniques. An on line version of this guide
is also available from the Help menu. For more information, see the topic Application
Examples on p. 5.
IBM SPSS Modeler Scripting and Automation.
scripting, including the properties that can be used to manipulate nodes and streams.
IBM SPSS Modeler Deployment Guide.
scenarios as steps in processing jobs under IBM® SPSS® Collaboration and Deployment
Services Deployment Manager.
IBM SPSS Modeler CLEF Developer’s Guide.
programs such as data processing routines or modeling algorithms as nodes in SPSS M odeler.
IBM SPSS Modeler In-Database Mining Guide.
database to improve performance and extend the range of analytical capabilities through
third-party algorithms.
IBM SPSS Modeler Server Administration and Performance Guide.
configure and administer IBM® SPSS® Modeler Server.
General introduction to using SPSS Modeler, including how
Descriptions of all the nodes used to create data mining
Descriptions of a ll the nodes used to
Descriptions of the mathematical foundations of the
The examples in this guide provide brief, targeted
Information on automating th e system through
Information on running SPSS Modeler streams and
CLEF provides the ability to integrate third-party
Information on how to use the power of your
Information on how to
IBM SPSS Modeler Administration Console User Guide.
console user interface for monitoring and configuring SPSS Modeler Server. The console is
implemented a
IBM SPSS Modeler Solution Publisher Guide.
s a plug-in to the Deployment Manager application.
component that enables organizations to publish streams for use outside of the standard
SPSS Modeler environment.
IBM SPSS Modeler CRISP-DM Guide.
for data mining with SPSS Modeler.
IBM SPSS Mod
eler Batch User’s Guide.
mode, including de tails of batch mode execution and command-line arguments. This guide
is available in PDF format only.
SPSS Modeler Premium Documentation
The SPSS Modeler Premium documentation suite (excluding installation instr uctions) is as
follows.
IBM SPSS Modeler Ent
SPSS Modeler, covering repos itory insta llation and co nfiguration, entity analytics nodes,
and administrative tasks.
IBM SPSS Modeler Social Network Analysis User Guide.
analysis with SPSS Mo
SPSS Modeler Text Analytics User’s Guide.
Modeler, covering the text mining nodes, interactive workbench, templates, and other
resources.
IBM SPSS Modeler Text Analytics Administration Console User Guide.
and using the console us er interface for monitoring and configuring IBM® SPSS® Modeler
Server for use with SPSS Modeler Text Analytics . The cons ole is implemented as a plug-in
to the Deployment Manager application.
ity Analytics User Guide.
deler, including group an alysis and diffusion analysis.
5
About IBM SPSS Modeler
Information on installing and using the
SPSS Modeler Solution Publis her is an add-on
Step-by-step guide to using the CRISP-DM methodology
Complete guide to using IBM SPSS Modeler in batch
Information on using entity analytics with
A guide to perform ing social network
Information on using text analytics with SPSS
Information on installing
Application Examples
While the d ata mining tools in SPS S Modeler can help solve a wide variety of business and
organizational pro blems, t
modeling methods and techniques. The data sets used here are much smaller than the enormous
data stores managed by some data miners, but the concepts and methods involved should be
scalable to real-world app
You can access the examples by clicking
Modeler. The data files and sam ple streams are installed in the Demos folder under the product
installation directory.
Database modeling examples.
Guide.
Scripting examples.
See the examples in the IBM SPSS Modeler Scripting and Automation Guide.
he application examples provide brief, targeted introductions to specific
lications.
Application Examples
on the Help menu in SPSS
For more information, see the topic Demos Folder on p. 6.
See the examples in the IBM SPSS Modeler In-Database Mining
6
Chapter 1
Demos Folder
The data files and sample streams used with the application examples are installed in the Demos
folder under the product installation directory. This folder can also be accessed from the
SPSS Modeler 15
recent directories in the File Open dialog box.
Figure 1-1
Selecting the Demos folder from the list of recently-used directories
IBM
program gr oup on the Windows Start menu, or by clicking Demos on the list of
New Features
New and Changed Features in IBM SPSS Modeler 15
From this release onwards, IBM® SPSS® Modeler has the following editions.
IBM® SPSS® Modeler Professional
IBM® SPSS® Modeler Premium
features to those supplied by SPSS Modeler Professional.
The new features for these edit ions are described in the following sections.
New features in IBM SPSS Modeler Professional
The IBM® SPSS® Modeler Professional edition adds the following features in this release.
is the new name for the existing SPSS Modeler product.
is a sepa r ately-licensed product that provides additio nal
Chapter
2
2
22
GLMM modeling node.
that: the target is linearly related to the factors and covariates via a specified link function; the
target can have a non-normal d is tribution; and the observations can be correlated. Generalized
linear mixed models cover a wide variety of models, from simple linear regression to co mplex
multilevel models for non-normal longitudinal data. For more information, see the topic New
Nodes in This Release on p. 10.
Support for maps in the Graphboard node.
number of map types. These include choropleths (wher e regions can be given different colors
or patterns to indicate different values) and point overlay maps (where geospatial points are
overlaid on the map).
IBM® SPSS® Modeler ships with several map file s, but you can use the Map Conversion Utility
to convert your existing map shapefiles for use with the Graphboard Template Chooser.
Netezza Time Series and Generalized Linear nodes.
Netezza® Analytics in - database mining: Time Series and Generalized Linear. For more
information, see the topic New Nodes in This Release on p. 10.
Netezza nodes enabled through Helper Applications.
nodes are now enabled in the same way as the other database modeling nodes.
Generalized linear mixed models (GLMMs) extend the linear model so
The Graphboard node now includes support for a large
Two new nodes are available for IBM®
The Netezza Analytics database modeling
Zooming in and out on the stream view.
from the standard size. This feature is particularly useful for gaining an overall view of a complex
stream, or for minimizing the number of pages needed to pri nt a stream. For more information,
see the topic Changing the icon size for a stream in Chapter 3 on p. 24.
© Copyright IBM Corporation 1994, 2012.
It is now possible to scale the entire stream view up or down
7
8
Chapter 2
Default settings for database connections.
and Ora cle dat
abase connections, as we ll as those already supported for IBM DB2 InfoSphere
You can now specify default settings for SQL Server
Warehouse.
Stream properties and optimization redesign.
The Options tab on the Stream Properties dialog box
has been redesigned to group the options into categories. The Optimizatio n options have also
moved from User Options to Stream Properties. For more information, see the topic Setting
Options for Streams in Chapter 5 on p. 54.
Node execution timing.
You can now set an option to display individ ual execution times for
the nodes in a stream. For more information, see the topic Viewing Node Execution Times in
Chapter 5 on p. 67.
You can also set an option (time_ecode_execution_log) in the server configuration file to record
these execution times in the message log.
Stream parameters in SQL queries from Database source node.
You can now include SPSS Modeler
stream parameters in SQL queries that you enter in the Database source node.
Expression Builder supports in-database functions.
If a stream connects to a database through a
Database source node and you use the Expression Builder with a downstream node, you can
include in-database functions from the connected database directly in the expression you are
building. For more in f ormation, see the t opic Selecting Functions in Cha pter 7 on p. 120.
IBM Cognos BI node enhancements.
The Cognos BI source node now supports importing C ognos
list reports as we ll as data, and additionally supports the use of parameters and filters.
For the Cognos BI source a nd export nodes, SPSS Modeler now automatically detects the version
of IBM Cognos BI in use.
Enhancements to Aggregate node.
The Aggregate node n ow supports several new aggregation
modes for aggregate fields: median, count, variance, and first and third quartiles.
Merge node supports conditional merge.
You can now perform input record merges that depend on
satisfying a condition. You can specify the condition directly in the n ode, or build the conditio n
using the Expression Builder.
Enhancements to in-database mining nodes for IBM DB2 InfoSphere Warehouse.
For in-database
mining with IBM DB2 InfoSphere Warehouse, the ISW Clustering node now supports the
Enhanced BIRCH algorithm in addition to demographic and Koho nen clustering. In addition, the
ISW Associ ation node provides a choice of layout for non-transactional (tabular) data.
Table compression for database export.
When exporting to a database, you can now specify table
compression options for SQL Server and Oracle database connections, as well as those already
supported for IBM DB2 InfoSphere Warehouse.
Bulk loading for database export.
Additional help information is available for database bulk loading
using an external loader program.
New Features
9
SQL generation enhancements.
timestamp, an
d string data types, in additi on to integer and real. With IBM Netezza databases, the
The Aggregate node now supports SQL generation for date, time,
Sample node supports SQL generation for simple and complex sampling, and the Binn ing node
supports SQL generation for all binning methods except Tiles.
In-database model scoring.
For I B M DB2 for z/OS, IBM Netezza and Teradata da tabases, it is
possible to enable SQL pushback of many of the model nuggets to carry out model scoring (as
opposed to in-database mining) within the database. To do this, you can install a scoring adapter
into the database. When you publish a model for the scoring adapter, the model is enabled to use
the user-defined function (UDF) capabilities of the database to perform the scoring.
A new configuration option, db_udf_enabled in options.cfg, causes the SQL generation option
to generate UDF SQL by default.
New format for database connection in batch mode.
The format for specifying a database connection
in batch mode has changed to a single argument, to be consistent with the way it is specified in
scripting.
Enhancements to SPSS Statistics integration.
are available on the Syntax tab th r ough the
On the Statistics Output node, additional procedures
Select a dialog
button. The Regres sion submenu
now supports Partial Least Squares regression, and there is a new Forecasting submenu with the
following op tions: Spectral Analysis, Sequence Charts, Autocorrelations, and Cross-correlations.
For mor e information, see the SPSS Statistics documentation.
The Syntax tab of the Statistics Output node also has a new option to generate a Statistics File
source node for importing the data that results fr om running a stream containing the node. This is
useful where a procedure writes fields such as scores to the active datas et in addition to displaying
output, as these fields would otherwise not be visible.
Non-root user on UNIX servers.
If you have SPS S Modeler Server installed on a UNIX server, you
can now install, configure, and start and stop SPSS Modeler Server as a non-root user without the
need for a pr ivate password database.
Deployed streams can now access IBM SPSS Collaboration and Deployment Services model
management features.
When a stream is deployed to IBM SPSS Collaboration and Deployment
Services as a str eam, it can now use the same model management features as it could if deployed
as a scenario. These features include evaluation, refresh, score, and champion/challenger.
Improved method of changing ODBC connection for SPSS Modeler stream and scenario job steps.
For
stream and scenario job steps in IBM SPSS Collaboration and Deployment Services, changes to
an ODBC connection and related logon credentials apply to all rela ted job steps. This means that
you no longer have to change the job steps one by one.
Choice of execution branch in deployed streams.
For stream job steps in IBM SPSS Collaboration
and Deployment Services, if the stream contains branches you can now choose one or more
stream branches to execute.
10
Chapter 2
New features in IBM SPSS Modeler Premium
IBM® SPSS® Modeler Premium is a separately-licensed product that provides additional features
to those supplied by IBM® SPSS® Modeler Professional. Previously, SPSS Mode ler Premi um
included only IBM® SPSS® Modeler Text Analytics . The full set of SPS S Modeler Premium
features is now as follows.
SPSS Modeler Text Analytics
IBM® SPSS® Modeler Entity Analytics
IBM® SPSS® Modeler Social Network Analysis
SPSS Modeler Text Analytics uses advanc ed linguistic technologies and Natural Language
Processing (NLP) to rapidly process a large variety of unstructured text data, extract and organize
the key concepts, and group these concepts into categories. Extracted concepts and categories
can be combined with existing structured data, such as demographics, and applied to modeling
using the full suite of IBM® SPSS® Modeler data mining tools to yield better and more focused
decisions.
IBM SPSS Modeler Entity Analytics adds a complet ely ne w dimension to SPSS Modeler
predictive analytics. Whereas predictive analytics attempts to predict future behavior from past
data, entity analytics focuses on improving the coherence and consistency of current data by
resolving identity conflicts within the records themselves. An identity can be that of an individual,
an organization, an object, or any other entity for which ambiguity might exist. Identity resolution
can be vital in a number of fields, including customer relationship management, fraud detection,
anti-money laundering, and national and international security.
IBM SPSS Modeler Social Network Analysis transforms information about relationships into
fields that characterize the social behavior of individuals and groups. Using data describing the
relationships underlying social networks, IBM SPSS Modeler Social Network Analysis identifies
social leaders who influence the behavior of others in the network. In addition, you can determine
which people are most affected by other network participants. By combining these results with
other measures, you can create comprehensive profiles of individuals on which to base your
predictive models. Models that inclu de this social information will perform better than models
that do not.
Note: SPSS Modeler Professional must be installed before installing any of the SPSS Modeler
Premium features.
New Nodes in This Release
IBM SPSS Modeler Professional
A generalized linear mixed model (GLMM) extends th e linear model so that the target
can have a non-normal distribution, is linearly related to the factors and covariates via
a specified link function, and so that the observations can be correlated. Generalized
linear mixed models cover a wide variety of models, from simple linear regression to
complex multilevel models for non-normal longitudinal data.
The Netezza Time Series node analyzes time series data and can predict future
behavior from past events.
The Netezza Generalized Linear model expands the linear regression model so that
the dependent variable is related to the predictor vari ables by means of a specified
link function. Moreover, the model all ows for the dependent variable to have a
non-normal distribution.
IBM SPSS Modeler Premium
The EA Export node is a terminal node that reads entity data from a data source and
exports the data to a repository for the purpose of entity resolution.
11
New Features
The Entity Analytics(EA) source node reads the resolved entities from th e repository
and passes th
is data to the stream for further processing, such as formatting into
a report.
The Streaming EA node compares new cases against the entity data in the repository.
The SNA Group Analysis node builds a model of a social net w ork based on input
data about the social groupings within the network. This technique identifies links
between the group members, and analyzes the interactions within the groups to
produce key performance indicators (KPIs). The KPIs can be used for purposes such
as churn prediction, anomaly detection, or group leader identification.
The SNA Diffusion Analysis node models the flow of information from a group
member to t heir social environment. A group member is assigned an initial weighting,
which is propagated across the network as a gradually reducing figure. This process
continues until each member of the network has been assigned a weighting relative to
the original group member, according to the amount of information that has reached
them. The individual member scores are then derived directly from these weightings.
In this way, for examp l e, a service provider could identify customers that are at a
higher risk of churn according to their relationship with a recent churner.
IBM SPSS Modeler Overview
Getting Started
As a data mining application, IBM® SPSS® Modeler offers a strategic approa ch to finding useful
relationships in large data sets. I n contrast to more traditional statistical methods, you do not
necessarily need to know what you are looking for when you start. You can explore y our data,
fitting different models and investigating different relationships, until you find useful information.
Starting IBM SPSS Modeler
To start the application, cli ck:
Start > [All] Programs > IBM SPSS Modeler15 > IBM SPSS Modeler15
Chapter
3
3
33
The main window is displayed after a few seconds.
Figure 3-1
IBM SPSS Modeler main application window
© Copyright IBM Corporation 1994, 2012.
12
Launching from the Command Line
You can use the command li ne of your operating system to launch IBM® SPSS® Modeler
as follows:
E
On a computer where IBM® SPSS® Modeler is installed, open a DOS, or command-prompt,
window.
E
To launch the SPSS Modeler interface in interactive mode, type the modelerclient command
followed by the re quired arguments; for example:
modelerclient -stream report.str -execute
The ava ilable arguments (flags) allow you to connect to a se r ver, load streams, run scripts, or
specify other parameters as needed.
Connecting to IBM SPSS Modeler Server
IBM® SPSS® Modeler can be run as a standalone application, or as a client connected to IBM®
SPSS® Modeler Server directly or to an SPSS Modeler Server or server cluster through the
Coordinator of Processes plug- in from IBM® SPSS® Collaboration and Deployment Services.
The current connection status is displayed at the bottom left of the SPSS Modeler window.
Whenever you want to connect to a server, you can ma nually enter the server name to which
you want to connect or select a name that you have previously defined. How ever, if you have I B M
SPSS Collaboration an d Deployme nt Services, you can search through a list of servers or server
clusters fro m the Server Login dialog box . The ability to browse through the Statistics services
running o n a network is made available through the Coordinator of Processes.
13
IBM SPSS Modeler Overview
Figure 3-2
Server Login dialog box
14
Chapter 3
To Connect to a Server
E
On the Tools menu, click
Server Login
. The Server Login dialog box opens. Alternatively,
double-click the connection status area of the SPSS Modeler window.
E
Using the dialog box, specify options to connect to the local server computer or select a connection
from the table.
Click
AddorEdit
to add or edit a connection . For mor e information, see the topic Adding and
Editing the IBM SPSS Modeler Server Connection on p. 14.
Click
Search
to acces s a server or server cluster in the Coordinator of Processes. For more
information, s ee the topic Searching for Servers in IBM SPSS Collaboration and Deployment
Services on p. 16.
Server table.
This table c ontains the set of defined server connections. The table displays the
default connection, server name, description, and port number. You can manually add a new
connection, as well as select or search for an existing connection. To set a particular server as the
default conne ction, select the check box in the Default column in the table for the connection.
Default data path.
Specify a path used for data on the server com puter. C lick the ellipsis button
to browse to the required location.
Set Credentials.
Leave this box unchecked to enable the single sign-on feature, which attempts
to log you in to the server using your local computer username and password details. If single
sign-on is not possible, or if you check this box to disable single sign-on (for example, to log in to
an administrator account), the following fields are enabled for you to enter your credentials.
User ID.
Password.
Domain.
Enter the user name with which to log on to the server.
Enter the passwo r d associa ted with the specified user name.
Specify the domain used to log on to the server. A domain name is required only when
the server computer is in a different Windows domain th an the client computer.
E
ClickOKto complete the connection.
To Disconnect from a Server
E
On the Tools menu, click
double-click the con
Server Login
. The Server Login dialog box opens. Alternatively,
nection status area of the SPSS Modeler window.
(...)
E
In the dialog box, select the Local Server and clickOK.
Adding and Editing the IBM SPSS Modeler Server Connection
You can manually edit or add a server connection in the Server Login dialog box. By clicking
Add, you can access an empty Add/Edit Server dialog box in which you can enter server
connection details. By selecting an existing connection and clicking Edit in the Server Login
dialog box, the Add/Edit Server dialog box opens with the details for that connection so that
you can make any changes.
IBM SPSS Modeler Overview
Note: You cannot edit a server connection that was added f r om IBM® SPSS® Collaboration
and Deploymen
t Services, since the name, port, and other deta ils are defined in IBM SPSS
Collaboration and Deployment Services.
15
Figure 3-3
Server Login
Add/Edit Server dialog box
To Add Server Connections
E
On the Tools menu, click
E
In this dialog box, click
E
Enter the server connection details and clickOKto save the connection and retu r n to the Server
Server Login
Add
. The Server Login Add/Ed it Server dialog box opens .
. The Server Login dialog box opens.
Login dialog box.
Server.
Specify an ava ilable server or select one from the list. The server computer can be
identified by an alphanumeric name (for example, myserver) or an IP address assigned to the
server computer (for example, 202.123.456.78).
Port.
Give the port number on which the server is listening. If the d efault does not work, ask
your system administrator for the corre ct port number.
Description.
Ensure secure connection (use SSL).
Enter an optional description for this server con ne ction.
Specifies whether an SSL (Secure Sockets Layer)
connection should be used. SSL is a commonly used protocol for securing data sent over a
network. To use this feature, SSL must be enabled on the server hosting IBM® SPSS®
Modeler Server. If necessary, contact your local administrator for details.
To Edit Server Connections
E
On the Tools menu, click
E
In this dialog box, select the connec tion you want to ed it and then click
Server Login
. The Server Login dialog box opens.
Edit
. The Server Login
Add/Edit Server dialog box opens.
E
Change the server connection details and clickOKto save the changes and return to the Server
Login dialog box.
16
Chapter 3
Searching for Servers in IBM SPSS Collaboration and Deployment Services
Instead of entering a server connection manually, you can select a server or server cluster available
on the network through the Coor dinator of Processes, available in IBM® SP SS® Collab oration
and Deployment Services. A server cluster is a group of servers from which the Coordinator of
Processes determines the server best suited to respond to a processing request.
Although you can ma nually add servers in the Ser ver Login dialog box, searching for available
servers lets you connect to servers without requiring that you know the correct server name and
port number. This information is autom atically provided. However, you still need the correct
logon information, such as username, domain, and pass word.
Note: If you do not have access to the Coordinator of Proc esses capability, you can still manually
enter the server name to which you want to connect or select a name that you have previously
defined. For more information, see the topic Adding and Editing the IBM SPSS Modeler Server
Connection on p. 14.
Figure 3-4
Search for Servers dialog box
To search for servers and clusters
E
On the Tools menu, click
E
In this dialog box, click
logged on to IBM SPSS Collaboration and Deployment Services when you attempt to browse
the Coordinator of Processes, you will be prompted to do so. For more information, see th e
topic Connecting to the Repository in Chapter 9 on p. 161.
E
Select the server or server cluster from th e list.
E
ClickOKto close the dialog box and add this connection to the table in the Server Login dialog box.
Changing the Temp Directory
Some operations perfor med by IBM® SPSS® Modeler Server may require temporary files to be
created. By default, IBM® SPSS® Modeler uses the system temporary directory to create temp
files. You can alter the location of the temporary directory using the following steps.
E
Create a new directory called spss and subdirectory called servertemp.
Server Login
Search
to open the Search for Ser ve r s dialog box. If you are not
. The Server Login dialog box opens.
E
Edit options.cfg, located in the /config directory of y our SPSS Modeler ins tallation directory. Edit
the temp_dire
E
After doing this, you must restart the SPSS Modeler Server service. You can do this by clicking
the
Services
ctory parameter in this file to read:
tab on your Windows Control Panel. Just stop the service and then start it to activate
the changes you made. Restarting the m achine will also restart the service.
All temp files will now be written to this new directory.
Note: The most common error when you are attempting to do this is to use the wrong type of
slashes. Because of SPSS Modeler’s UNIX history, forward slashes are used.
Starting Multiple IBM SPSS Modeler Sessions
If you need to launch more than one IBM® SPSS® Modeler s ession at a time, you must make
some changes to your IBM® SPSS® Modeler and Windows settings. For example, you may
need to do th is if you have two separate se r ver license s and want to run two streams against two
different servers from the same client machine.
To enable multiple SPSS Modeler sessions:
IBM SPSS Modeler Overview
temp_directory, "C:/spss/servertemp"
17
.
E
Click:
Start > [All] Programs > IBM SPSS Modeler15
E
On the IBM SPSS Modeler15 shortcut (the one with the icon), right-click and select
E
In the
Target
text box , add
E
In Windows Explorer, select:
Tools > Folder Options...
E
On the File Types tab, select the SPSS Modeler Stream option and click
E
In the Edit File Type dialog box, select
E
In the
Application used to perform action
-noshare
to the end of the string.
Open with SPSS Modeler
text box, add
IBM SPSS Modeler Interface at a Glance
At each point in the data mining proce ss, IBM® SPSS® Modeler’s easy-to-use interface invites
your specific business e xpertise. Modeling algorithms, such as prediction, classification,
segmentation, and association detection, ensure powerful and accurate models. Model results
can easily be deployed a nd read into databases, IBM® SPSS® Statistics, and a wide variety
of other applications.
-noshare
and click
before the
Advanced
Edit
.
-stream
Properties
.
argument.
.
Working with SPSS Modeler is a three-step process of working with data.
First, you read data into SPSS Modeler.
Next, you run the data through a series of manipulations.
Finally, you send the data to a destination.
18
Chapter 3
This sequ ence of operations is known as a data stream because the data flows record by record
from the sourc
e through each manipulation and, finally, to the destination—either a model or
type of data output.
Figure 3-5
A simple stream
IBM SPSS Modeler Stream Canvas
The stream canvas is the largest area of the IBM® SPSS® Modeler window and is where you will
build and manipulate data streams.
Streams are created by drawing diagrams of data operations relevant t
main canvas in the interface. Each operation is represented by an icon or node, and the nodes are
linked together in a stream representing the flow of data through each operation.
You can work with multiple streams at one time in SPSS Modeler, either i
canvas or by opening a new stream canvas. During a sessi on, streams are stored in the Streams
manager, at the upper right of the SPSS Modeler window.
o your business on the
n the same stream
Nodes Palette
Most of the data and modeling tools in IBM® SPSS® Modeler reside in the Nodes Palette, acr oss
the b ottom o f the window below the stream canvas.
For example, the Record Ops palette tab contains nodes that you can use to perform operations
on the data records, such as selecting, merging, and appending.
To add nodes to the canvas, double-click icons from the Nodes Palette or drag and drop them
onto the canvas. You then connect them to create a stream, representing the flow of data.
Figure 3-6
Record Ops tab on the nodes palette
Each palette tab contains a collection of related nodes used for different p hases of stream
operations, such as :
Sources.
Record Ops.
appending.
Nodes bring data into SPSS Modeler.
Nodes perform operations on data records, such as selecting, merging, an d
IBM SPSS Modeler Overview
Field Ops.
Nodes perform operations on data fields, such as filtering, deriving new fields, and
determining the measurement level for given fields.
Graphs.
Nodes graphically display data before and after modeling. Graphs include plots,
histograms, web nodes, and evaluation charts.
Modeling.
des use the modeling algorithms available in SPSS Modeler, such as neural nets ,
No
decision trees, clustering algorithms, and data sequencing.
Database Modeling.
Nodes use the modeling algorithms available in Microsoft SQL Server,
IBM DB2, and Oracle database s.
Output.
Nodes produce a variety of output for d ata, charts, and model results that can be
viewed in SPSS Modeler.
Export.
es prod uce a variety of output that can be viewed in external applications, such
Nod
as IBM® S PSS® Data Collection or Excel.
SPSS Statistics.
Nodes import data from, or export data to, IBM® SPSS® Stat is tics, as well as
running SPSS Statistics procedures.
As you become more familiar with SPSS Modeler, you can customize the palette contents for
your own use. For more information, see the topic Customizing the Nodes Palette in Chapter 12
on p. 223.
Located below the Nodes Palette, a report pane provides feedback on the progress of various
operations, such as when data is being read into t he data stream. Also located below the Nodes
Palette, a status pane provides info r mation on what the application is currently doing, as well as
indications of when user feedback is required.
19
IBM SPSS Modeler Managers
At the top right of the window is the managers pane . This has three tabs, which are used to
manage streams, output and models.
You can use the Streams tab to open, rename, save, and dele te the streams created in a session.
Figure 3-7
Streams tab
The Outputs tab contains a variety of files , such as graphs and tables, produced by stream
operations in IBM® SPSS® Modeler. You can display, save, rename, and close the tables, graphs,
and reports listed on this tab.
20
Chapter 3
Figure 3-8
Outputs tab
The Models tab is the most powerful of the manager tabs. This tab contains all model nuggets,
which contain the models generated in SPSS Modeler, for the current session. These models can
be browsed directly from the Models tab or added to the stream in the c anvas.
Figure 3-9
Models tab containing model nuggets
IBM SPSS Modeler Projects
On the lower right side of the window is the project pane, used to create and manage data mining
projects (groups of files related to a data mining task). There are two ways to view projects you
in IBM® SPSS® Modeler—in the Classes view and the CRISP-DM view.
create
The CRISP-DM tab provides a way to organize projects according to the Cross-Industry
Standard Process for Data Mining, an industry-proven, nonproprietary methodology. For both
enced and first-time data miners, using the CRISP-DM tool will help you to better o rganize
experi
and communicate your efforts.
Loading...