Oracle9i Data Mining Concepts

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  • 1. Oracle9i Data Mining ConceptsRelease 9.2.0.2 October 2002 Part No. A95961-02

2. Oracle9i Data Mining Concepts, Release 9.2.0.2Part No. A95961-02Copyright 2002 Oracle Corporation. All rights reserved.The Programs (which include both the software and documentation) contain proprietary information of Oracle Corporation; they are provided under a license agreement containing restrictions on use and disclosure and are also protected by copyright, patent and other intellectual and industrial property laws. Reverse engineering, disassembly or decompilation of the Programs, except to the extent required to obtain interoperability with other independently created software or as specified by law, is prohibited.The information contained in this document is subject to change without notice. If you find any problems in the documentation, please report them to us in writing. Oracle Corporation does not warrant that this document is error-free. Except as may be expressly permitted in your license agreement for these Programs, no part of these Programs may be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without the express written permission of Oracle Corporation.If the Programs are delivered to the U.S. Government or anyone licensing or using the programs on behalf of the U.S. Government, the following notice is applicable:Restricted Rights Notice Programs delivered subject to the DOD FAR Supplement are "commercial computer software" and use, duplication, and disclosure of the Programs, including documentation, shall be subject to the licensing restrictions set forth in the applicable Oracle license agreement. Otherwise, Programs delivered subject to the Federal Acquisition Regulations are "restricted computer software" and use, duplication, and disclosure of the Programs shall be subject to the restrictions in FAR 52.227-19, Commercial Computer Software - Restricted Rights (June, 1987). Oracle Corporation, 500 Oracle Parkway, Redwood City, CA 94065.The Programs are not intended for use in any nuclear, aviation, mass transit, medical, or other inherently dangerous applications. It shall be the licensee's responsibility to take all appropriate fail-safe, backup, redundancy, and other measures to ensure the safe use of such applications if the Programs are used for such purposes, and Oracle Corporation disclaims liability for any damages caused by such use of the Programs.Oracle is a registered trademark, and Oracle9i is a trademark or registered trademark of Oracle Corporation. Other names may be trademarks of their respective owners. 3. ContentsSend Us Your Comments .................................................................................................................. viiPreface............................................................................................................................................................ ix1 Basic ODM Concepts 1.1 New Features and Functionality .........................................................................................1-2 1.2 Oracle9i Data Mining Components ....................................................................................1-3 1.2.1Oracle9i Data Mining API.............................................................................................1-3 1.2.2Data Mining Server ........................................................................................................1-3 1.3 Data Mining Functions ......................................................................................................... 1-4 1.3.1Classification...................................................................................................................1-4 1.3.2Clustering ........................................................................................................................1-6 1.3.3Association Rules ...........................................................................................................1-7 1.3.4Attribute Importance ..................................................................................................... 1-8 1.4 ODM Algorithms................................................................................................................... 1-9 1.4.1Adaptive Bayes Network ............................................................................................ 1-10 1.4.2Naive Bayes Algorithm ............................................................................................... 1-12 1.4.3Model Seeker................................................................................................................. 1-14 1.4.4Enhanced k-Means Algorithm ...................................................................................1-15 1.4.5O-Cluster Algorithm.................................................................................................... 1-17 1.4.6Predictor Variance Algorithm .................................................................................... 1-18 1.4.7Apriori Algorithm ........................................................................................................1-18 1.5 Data Mining Tasks .............................................................................................................. 1-19 1.5.1Model Build...................................................................................................................1-20 iii 4. 1.5.2Model Test ..................................................................................................................... 1-211.5.3Computing Lift ............................................................................................................. 1-221.5.4Model Apply (Scoring) ................................................................................................ 1-221.6ODM Objects and Functionality........................................................................................1-241.6.1Physical Data Specification .........................................................................................1-241.6.2Mining Function Settings ............................................................................................1-251.6.3Mining Algorithm Settings .........................................................................................1-261.6.4Logical Data Specification ........................................................................................... 1-271.6.5Mining Attributes......................................................................................................... 1-271.6.6Data Usage Specification ............................................................................................. 1-271.6.7Mining Model ............................................................................................................... 1-281.6.8Mining Results ..............................................................................................................1-281.6.9Confusion Matrix.......................................................................................................... 1-291.6.10 Mining Apply Output..................................................................................................1-301.7Missing Values ..................................................................................................................... 1-321.7.1Missing Values Handling............................................................................................1-321.8Discretization (Binning)...................................................................................................... 1-321.8.1Numerical and Categorical Attributes ......................................................................1-321.8.2Automated Binning......................................................................................................1-331.8.3Data Preparation...........................................................................................................1-331.9PMML Support ....................................................................................................................1-372 ODM Programming2.1Compiling and Executing ODM Programs .......................................................................2-12.2Using ODM to Perform Mining Tasks ............................................................................... 2-22.2.1Build a Model.................................................................................................................. 2-22.2.2Perform Tasks in Sequence ........................................................................................... 2-32.2.3Find the Best Model ....................................................................................................... 2-32.2.4Find and Use the Most Important Attributes............................................................. 2-42.2.5Apply a Model to New Data.........................................................................................2-53 ODM Basic Usage3.1Using the Short Sample Programs ...................................................................................... 3-23.2Building a Model ................................................................................................................... 3-23.2.1Before Building an ODM Model .................................................................................. 3-2 iv 5. 3.2.2 Main Steps in ODM Model Building...........................................................................3-3 3.2.3 Connect to the Data Mining Server .............................................................................3-3 3.2.4 Describe the Build Data................................................................................................. 3-4 3.2.5 Create the MiningFunctionSettings Object.................................................................3-5 3.2