Develop Predictive Models Using Your Business Expertise
Contents
1. CARMA Filter sort and subset association models with the new association model viewer Use Apriori sequence and CARMA generated models for scoring Data reduction Factor analysis and principal components analysis View model equation and advanced Statistical output a Combine models for greater accuracy through meta modeling Multiple models can be combined or one model can be used directly for building a second model Import PMML generated models created in other tools such as AnswerTree and SPSS for Windows Clementine External Module Interface CEMI for custom algorithms Add data access modeling and graphics Create node palettes and generated model palettes including PMML generated models created in other tools using custom CEMI icons a An algorithm user manual is included which explains the theories and methods behind the algorithms included in Clementine Evaluation a Easily evaluate models using lift gains profit and response graphs Use a one step process that shortens project time when evaluating multiple models Define hit conditions and scoring expressions to interpret model performance Deployment Clementine offers a broad array of deployment capabilities to meet your organization s needs Models built in Clementine can be directly deployed into other SPSS predictive applications and into other vendors technologies Clementine Solution Publisher optio2. and its algorithms are calibrated and verified to deliver powerful data mining results With Clementine you can be assured of having the analytical techniques you need to attain the most reliable results See more results more quickly with Clementine 8 5 Clementine 8 5 offers features that further increase the versatility this solution has always offered improving your data mining productivity Building on its existing open standards based architecture Clementine 8 5 enables organizations to further leverage their existing technology investments Organizations using Microsoft SQL Server 2000 Analysis Services can build Microsoft decision trees directly from the Clementine interface Companies using Sun Solaris UltraSPARC servers will enjoy improved performance in processing large datasets because Clementine 8 5 supports the 64 bit port on these servers Organizations can browse association models and automatically deploy other models built in Clementine into IBM DB2 Data Warehouse Edition Customers of DataDistilleries B V which is now part of SPSS Inc can author and automatically deploy streams from Clementine 8 5 into the predictive applications they currently use To deepen the level of insight that can be gained from data mining Clementine 8 5 adds a new association viewer It also incorporates CARMA a high speed association detection algorithm that delivers not only faster processing but als
3. based on conditional criteria and calculating new fields Specialized manipulations for showing the history of values and converting set variables into flag variables Automatically bin data based on n tiles mean and standard deviation rank or a fixed width Re group or collapse categories and transform one set of discrete values to another Customize the natural order of fields Merge records using any of the following types of joins Inner join Full outer join Partial outer join both left and right Anti join the opposite of an inner join Features are subject to change based on the final product release _ Symbol indicates a new feature Separately priced modules Modeling Prediction and classification Neural networks multi layer perceptrons trained using error back propagation with momentum radial basis function and Kohonen networks Browse the importance of the predictors Decision trees and rule induction C5 0 and Classification and Regression Trees C amp RT Browse and interact with decision trees Browse collapse and expand decision rules Linear regression logistic regression and multinomial logistic regression View model equation and advanced Statistical output Clustering and segmentation Kohonen network K means and TwoStep View summary statistics and distributions for fields between clusters Association detection GRI Apriori sequence
4. easy to use project manager that enables you to smoothly execute each step in your data mining projects using this methodology The diagram below shows the CRISP DM process Following the diagram is a summary of the capabilities of the Clementine solution that apply to each step of the CRISP DM process as well as a brief discussion of other features that make Clementine the data mining workbench of choice The CRISP DM process as shown above enables data miners to efficiently implement data mining projects that yield measurable business results Business understanding Clementine s visual interface makes it easy for your data miners to apply business knowledge to data mining projects In addition optional business specific Clementine Application Templates CATs are available that when used in conjunction with Clementine deliver data mining results faster CATs support flat files as well as commonly used database layouts conforming to data warehouse standards The CATs include the a CRM CAT a Telco CAT m Fraud CAT a Microarray CAT Data understanding To provide a comprehensive first look at your data Clementine enables you to auto matically generate subsets of data from graphs and tables Through the data audit node you can create summary Statistics histograms and distribution graphics for each data field and display them in an easy to read matrix a Visually interact with your data S
5. the client Generate SQL from linear regression and factor generated models Generate SQL from decision trees and rule sets a Use the bulk loading capabilities of your database Increase performance during data export by using a bulk loader program that s specific to your database Fine tune various options including row wise or column wise binding for loading via ODBC and batch size setting for batch commits to the database Bo Cae Scalability and integration Scalability m Use in database mining and server tier processing to leverage parallel database implementations a Minimize network traffic via intelligent field projection Clementine pulls data only as needed from your data warehouse and passes only relevant results to the client Integration a Clementine integrates with SPSS and AnswerTree and supports Cleo through a built in Wizard a It also integrates with other databases market automation and software tools On Sun Solaris systems Clementine 8 5 supports Kerberos security a network authentication protocol and runs as non root m Clementine 8 5 supports the export of streams to SPSS predictive applications that incorporate products formerly offered by DataDistilleries B V m In addition Clementine 8 5 integrates with Microsoft Analysis Services for building decision trees IBM DB2 Warehouse Edition for deploying models to Intelligent Miner Scoring and the viewing of Clementine mode
6. Clementine 8 5 Specifications gt Develop Predictive Models Using Your Business Expertise Clementine is an integrated data mining workbench popular worldwide with data miners and business analysts alike Clementine supports the entire data mining process enabling users to quickly access and prepare data for modeling rapidly build and compare models and then deploy models into real time operational environments Clementine seamlessly integrates data mining results with other business systems and processes giving decision makers a clearer view of current conditions and insight into future events Clementine s highly visual user interface makes train of thought analysis possible Clementine produces streams a visual map of your data mining steps to automatically document the analytical process By interacting with a stream data miners can add business knowledge the key to successful data mining to the data mining process The Clementine interface makes it easy to explore ideas or intuitive hunches And because it allows you to focus on knowledge discovery rather than on performing technical tasks such as writing code you achieve results quickly Select from an unparalleled breadth of techniques Clementine offers a full range of machine learning and statis tical techniques for clustering classification association and prediction SPSS Inc has more than 35 years experi ence in predictive analytics
7. Server with Service Pack 5 cannot be installed on Windows NT Terminal Server or Sun Solaris Version 7 or later with UltraSPARC 2 hardware or better Hardware 500MHz processor or faster Memory 512MB RAM Minimum free drive space 7OOMB A graphics adapter with 800 x 600 resolution SVGA or higher capable of displaying at least 256 colors Anetwork adapter running the TCP IP protocol Repository the system requires a database to serve as a repository for published content framework settings and other information The following databases are supported Microsoft SQL Server 2000 Oracle 8i version 8 1 7 Data warehouse the system can be configured to access data from a data warehouse or database The system has only been tested with SQL Server 2000 and Oracle 8i databases Web client content is delivered to clients as standard HTML pages Supported browsers include Internet Explorer version 5 5 with Service Pack 2 or version 6 0 for Windows Internet Explorer version 5 2 for Macintosh Netscape 6 2 Text Mining for Clementine optional Client version requirements Clementine 7 1 or later Operating system Windows 2000 Windows 2000 Professional or Windows NT 4 0 with Service Pack 6 or later Memory 512MB RAM Minimum free disk space 85MB plus space for databases Web Browser Internet Explorer 5 0 or later or Netscape 6 0 or later is required to use the View
8. ace 128MB required for installation Additional free disk space is required to run the program for temporary files 1GB is recommended For Clementine Solution Publisher Runtime the minimum free disk space required to install the software is 64MB plus at least twice the disk space of the amount of data to be processed A network adapter running TCP IP protocol a A CD ROM drive is required for installation Clementine uses a highly scalable three tiered architecture for data mining as shown in this diagram The Clementine Client tier shown at the bottom of the illustration passes stream description language SDL to Clementine Server Clementine Server then analyzes these particular tasks to determine which tasks it can push to the database After the database runs the tasks it can process it passes only the relevant aggregated tables to Clementine Server If you are using a CEMI such as Text Mining for Clementine or Capri Clementine Server passes the relevant tasks to that particular external process Features are subject to change based on the final product release _ Symbol indicates a new feature Separately priced modules Cleo optional Web server Cleo requires at least one server computer that meets the following minimum requirements Using additional processors faster processors and more RAM will improve performance Operating system Server versions of Windows 2000 or 2003 Windows NT 4 0
9. elect a node or field and view information in a table Create histograms distributions line plots and point plots Use Web association detection Display 3 D panel and animated graphs Data preparation a Bring data into Clementine using a variety of methods and sources Access structured tabular data Use the security controls of your selected database or operating system to ensure data security Access ODBC compliant data sources The included SPSS Data Access Pack enables you to work with data in Oracle Microsoft SQL Server IBM DB2 Sybase and Informix databases Import delimited and fixed width text SPSS and SAS 6 7 8 and 9 files Analyze unstructured textual data Automatically extract concepts from documents and from text notes in databases using Text Mining for Clementine Analyze Web site data Automatically extract Web site events from Web logs using Web Mining for Clementine Data output Work with delimited and fixed width text ODBC Microsoft Excel SPSS and SAS 6 7 8 and 9 files Choose from various data cleaning options Remove or replace invalid data Automatically fill in missing values Manipulate data Work with complete record and field operations including Field filtering naming derivation and value replacement Record selection sampling merging and concatenation sorting aggregation and balancing deriving new fields
10. er node Server version requirements Operating system Server or Professional versions of Windows 2000 or 2003 Windows NT Server 4 0 with Service Pack 6 or later or Solaris 8 or 9 Memory 256MB RAM Minimum free disk space 85MB plus space for databases Web Mining for Clementine optional Client version requirements Clementine 7 2 or later Operating system Windows XP or Server or Professional versions of Windows 2000 or 2003 Memory 512MB RAM Minimum free disk space twice the amount of raw Web data being processed Server version requirements Operating system Windows Professional versions of Windows 2000 or 2003 Memory 512MB RAM Minimum free disk space twice the amount of raw Web data being processed Requirements for the Japanese language version differ See www spss com lexiquest systemrequirements To learn more please visit www spss com For SPSS office locations and telephone numbers go to www spss com worldwide SPSS is a registered trademark and the other SPSS products named are trademarks of SPSS Inc All other names are trademarks of their respective owners Copyright 2004 Integrated Solutions Ltd CLM85SPC 0404 Clementine Application Templates optional a Clementine 7 2 a Memory 512MB RAM recommended Capri for Clementine optional Plug in algorithm for detecting sequences a Operating system Windows 98 2000 2003 Windows NT 4 0 with Service Pack 3 or later or Sun Solari
11. ls with Intelligent Miner Visualization E Server 8 System requirements Clementine Client a Operating system Microsoft Windows Me Windows XP Home or Professional Windows NT 4 0 with Service Pack 6 Windows 2000 or 2003 Memory 256MB RAM recommended 512MB recommended when using CATs or other large datasets Minimum free disk space 320MB A CD ROM drive is required for installation Web browser Internet Explorer version 5 x or later or Netscape 6 or later for running the online help system Clementine Server Clementine Solution Publisher Runtime optional and Clementine Batch Mode Operating system Windows 2000 Professional or Advanced Server Windows 2003 Server or Windows NT 4 0 with Service Pack 6 or later Sun Solaris 2 7 2 8 or 2 9 HP UX 11i IBM AIX 4 3 3 or 5 2 or OS 400 on the IBM eServer iSeries V5R2 with OS 400 Portable Applications Solution Environment PASE 5722 SS1 Option 33 External Processing e g modeling algorithms lt 7 Clementine Server AN W Client Results Hardware Pentium compatible processor SPARC for Solaris Sun UltraSPARC 2 hardware or better if running on Solaris HP Workstation for HP UX PA RISC processor HP 9000 server if running on HP UX IBM RS 6000 for AIX PowerPC 233MHz or better if running on AIX or IBM iSeries server a Memory 256MB RAM minimum 512MB recommended Minimum free drive sp
12. nal Automate the export of all operations including data access data manipulations model scoring including combinations of models and post processing Work in a runtime environment for executing image files on target platforms Easily update solutions through small image files Cleo optional a Web based solution for rapid model deployment Enable multiple users to simultaneously access and immediately score single records multiple records or an entire database through a customizable browser based interface a Clementine Batch Mode Automate production tasks while working outside the user interface Automate Clementine processes from other applications or scheduling systems Generate encoded passwords Launch commands using a command file a Scripting Automate command line scripts or scripts associated with Clementine streams to automate repetitive tasks in the user interface Scripts generally perform the same types of actions that otherwise are carried out using a mouse or keyboard Execute selected lines from a stream SuperNode or stand alone script using an icon on the toolbar Update stream parameters within a standalone script Refresh source nodes automatically upon stream execution Export generated models as PMML Perform in database scoring which eliminates the need for and costs associated with transferring data or performing calculations on
13. o more detailed information With Clementine there s good news for your IT staff Clementine is an open standards based system that easily integrates with your organization s existing operational systems and databases Clementine leverages your database investment by performing much of the data preprocessing tasks typically 80 90 percent of your data mining effort within the database Because preprocessing occurs on the database tier rather than on the server or client tiers you save time maximize resources and minimize network traffic SPSS offers several deployment options to meet your needs for in database or real time scoring Clementine exports not only the model but also all data mining steps including data access modeling and post pro cessing saving your organization time and money Clementine also uses the industry standard predictive model markup language PMML which means that language generated in Clementine can be easily embedded in other systems As a result you can efficiently publish processes or streams and transparently deliver results to other software applications Features CRISP DM Help your company s analysts and data miners focus on business problem solving rather than on the data mining technology Clementine supports the CRoss Industry Standard Process for Data Mining CRISP DM the de facto industry standard at every step of the process Clementine includes an
14. s 2 6 Hardware Pentium compatible processor or higher for Windows or SPARC for Solaris a Memory 128MB RAM Minimum free drive space 3MB a A CD ROM drive is required for installation
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