• Document: Data Mining. SPSS Clementine Clementine Overview. Spring 2010 Instructor: Dr. Masoud Yaghini. Clementine
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Data Mining SPSS Clementine 12.0 1. Clementine Overview Spring 2010 Instructor: Dr. Masoud Yaghini Clementine Outline  Introduction  Types of Models  Clementine Interface  Projects  References Clementine Introduction Clementine Introduction  Three of the common data mining tools – SPSS Clementine – SAS-Enterprise Miner – STATISTICA Data Miner  The most popular and the oldest data mining tool package on the market today is SPSS Clementine Clementine Introduction  SPSS Clementine – the most mature among the major data mining packages on the market today.  Since 1993, many thousands of data miners have used Clementine to create very powerful models for business.  It was the first data mining package to use the graphical programming user interface.  It enables you to quickly develop data mining models and deploy them in business processes to improve decision making. Clementine Introduction  The Clementine package was integrated with CRISP- DM to help guide the modeling process flow.  Clementine supports the entire data mining process. Clementine Clementine Documentation  Clementine User’s Guide – General introduction to using Clementine.  Clementine Source, Process, and Output Nodes – Descriptions of all the nodes used to read, process, and output data in different formats.  Clementine Modeling Nodes – Descriptions a variety of modeling methods in Clementine  Clementine Applications Guide – The examples in this guide provide brief, targeted introductions to specific modeling methods and techniques.  Clementine Algorithms Guide – Descriptions of the mathematical foundations of the modeling methods used in Clementine.  CRISP-DM 1.0 Guide – Step-by-step guide to data mining using the CRISP-DM methodology. Clementine Application Examples  While the data mining tools in Clementine can help solve a wide variety of business and organizational problems, the application examples provide brief, targeted introductions to specific modeling methods and techniques.  You can access the examples by choosing Application Examples from the Help menu in Clementine Client.  The data files and sample streams are installed in the Demos folder under the product installation directory. Clementine 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 Clementine 12.0 program group under SPSS Inc on the Windows Start menu. Clementine Changing the Temp Directory  Some operations performed by Clementine may require temporary files to be created.  By default, Clementine uses the system temporary directory to create temp files. Clementine Changing the Temp Directory  To alter the location of the temporary directory using the following steps: – Create a new directory called clem and subdirectory called servertemp. – Edit options.cfg, located in the /config directory of your Clementine installation directory. – Edit the temp_directory parameter in this file to read: temp_directory, "C:/clem/servertemp". – After doing this, you must restart the Clementine Server service. You can do this by clicking the Services tab on your Windows Control Panel. Just stop the service and then start it to activate the changes you made. Restarting the machine will also restart the service. – All temp files will now be written to this new directory. Clementine Types of Models Clementine Types of Models  In Clementine 12.0, models are packaged into following modules: – Classification module  The Classification module helps organizations for prediction – Association module  Association models associate a particular conclusion (such as the decision to buy something) with a set of conditions. – Segmentation module  The Segmentation module is recommended in cases where the specific result is unknown Clementine Classification Module  Classification module is included: – Decision Trees  C&R Tree  QUEST  CHAID  C5.0 – Decision List – Neural Networks – Regression  Linear regression  Logistic regression – Bayesian Network – Support Vector Machine (SVM) Clementine Association Module  Association module is included: – Generalized Rule Induction (GRI) – Apriori mo

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