Java Data Mining: Strategy, Standard, and Practice: A Practical Guide for architecture, design, and implementation
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Table of contents
- Contentsvii
- Prefacexvii
- Guide to Readersxxi
- Part I : Strategy1
- Chapter 1. Overview of Data Mining3
- 1.1 Why Data Mining Is Relevant Today?4
- 1.2 Introducing Data Mining6
- 1.3 The Value of Data Mining20
- 1.4 Summary23
- References24
- Chapter 2. Solving Problems in Industry25
- 2.1 Cross-Industry Data Mining Solutions26
- 2.2 Data Mining in Industries41
- 2.3 Summary47
- References47
- Chapter 3. Data Mining Process51
- 3.1 A Standardized Data Mining Process52
- 3.2 A More Detailed View of Data Analysis and Preparation60
- 3.3 Data Mining Modeling, Analysis, and Scoring Processes70
- 3.4 The Role of Databases and Data Warehouses in Data Mining74
- 3.5 Data Mining in Enterprise Software Architectures75
- 3.6 Advances in Automated Data Mining81
- 3.7 Summary82
- References83
- Chapter 4. Mining Functions and Algorithms85
- 4.1 Data Mining Functions86
- 4.2 Classification88
- 4.3 Regression89
- 4.4 Attribute Importance91
- 4.5 Association93
- 4.6 Clustering97
- 4.7 Summary100
- References101
- Chapter 5. JDM Strategy103
- 5.1 What Is the JDM Strategy?104
- 5.2 Role of Standards110
- 5.3 Summary114
- References114
- Chapter 6. Getting Started117
- 6.1 Business Understanding118
- 6.2 Data Understanding119
- 6.3 Data Preparation121
- 6.4 Modeling123
- 6.5 Evaluation127
- 6.6 Deployment127
- 6.7 Summary129
- References129
- Part II : Standards131
- Chapter 7. Java Data Mining Concepts133
- 7.1 Classification Problem134
- 7.2 Regression Problem157
- 7.3 Attribute Importance160
- 7.4 Association Rules Problem162
- 7.5 Clustering Problem165
- 7.6 Summary170
- References170
- Chapter 8. Design of the JDM API173
- 8.1 Object Modeling of Data Mining Concepts174
- 8.2 Modular Packages187
- 8.3 Connection Architecture188
- 8.4 Object Factories190
- 8.5 Uniform Resource Identifiers for Datasets192
- 8.6 Enumerated Types192
- 8.7 Exceptions194
- 8.8 Discovering DME Capabilities196
- 8.9 Summary197
- References197
- Chapter 9. Using the JDM API199
- 9.1 Connection Interfaces200
- 9.2 Using JDM Enumerations213
- 9.3 Using Data Specification Interfaces214
- 9.4 Using Classification Interfaces218
- 9.5 Using Regression Interfaces235
- 9.6 Using Attribute Importance Interfaces240
- 9.7 Using Association Interfaces243
- 9.8 Using Clustering Interfaces249
- 9.9 Summary256
- References257
- Chapter 10. XML Schema259
- 10.1 Overview260
- 10.2 Schema Elements260
- 10.3 Schema Types262
- 10.4 Using PMML with the JDM Schema267
- 10.5 Use Cases for JDM XML Schema and Documents270
- 10.6 Summary271
- References271
- Chapter 11. Web Services273
- 11.1 What is a Web Service?274
- 11.2 Service-Oriented Architecture277
- 11.3 JDM Web Service278
- 11.4 Enabling JDM Web Services Using JAX-RPC293
- 11.5 Summary296
- References297
- Part III : Practice299
- Chapter 12. Practical Problem Solving301
- 12.1 Business Scenario 1: Targeted Marketing Campaign302
- 12.2 Business Scenario 2: Understanding Key Factors321
- 12.3 Business Scenario 3: Using Customer Segmentation325
- 12.4 Summary338
- References339
- Chapter 13. Building Data Mining Tools Using JDM341
- 13.1 Data Mining Tools342
- 13.2 Administrative Console346
- 13.3 User Interface to Build and Save a Model356
- 13.4 User Interface to Test Model Quality376
- 13.5 Summary385
- Chapter 14. Getting Started with JDM Web Services387
- 14.1 A Web Service Client in PhP387
- 14.2 A Web Service Client in Java397
- 14.3 Summary406
- References406
- Chapter 15. Impacts on IT Infrastructure407
- 15.1 What Does Data Mining Require from IT?408
- 15.2 Impacts on Computing Hardware409
- 15.3 Impacts on Data Storage Hardware411
- 15.4 Data Access414
- 15.5 Backup and Recovery416
- 15.6 Scheduling416
- 15.7 Workflow417
- 15.8 Summary419
- References419
- Chapter 16. Vendor Implementations421
- 16.1 Oracle Data Mining421
- 16.2 KXEN (Knowledge Extraction Engines)431
- 16.3 Guidelines for New Implementers440
- 16.4 Process for New JDM Users446
- 16.5 Summary446
- References446
- Part IV : Wrapping Up449
- Chapter 17. Evolution of Data Mining Standards451
- 17.1 Data Mining Standards452
- 17.2 Java Community Process456
- 17.3 Why So Many Standards?457
- 17.4 Directions for Data Mining Standards461
- 17.5 Summary463
- References464
- Chapter 18. Preview of Java Data Mining 2.0465
- 18.1 Transformations466
- 18.2 Time Series469
- 18.3 Apply for Association471
- 18.4 Feature Extraction472
- 18.5 Statistics473
- 18.6 Multi-target Models474
- 18.7 Text Mining475
- 18.8 Summary476
- References477
- Chapter 19. Summary479
- Further Reading483
- Glossary485
- Index499
- About the Authors519
Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component. This book is the essential guide to the usage of the JDM standard interface, written by contributors to the JDM standard.
The book discusses and illustrates how to solve real problems using the JDM API. The authors provide you with:
* Data mining introduction—an overview of data mining and the problems it can address across industries; JDM’s place in strategic solutions to data mining-related problems;
* JDM essentials—concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects;
* JDM in practice—the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API.
* Free, downloadable KJDM source code referenced in the book available here
* Data mining introduction—an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems;
* JDM essentials—concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects;
* JDM in practice—the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API.
* Free, downloadable KJDM source code referenced in the book available here
The book discusses and illustrates how to solve real problems using the JDM API. The authors provide you with:
* Data mining introduction—an overview of data mining and the problems it can address across industries; JDM’s place in strategic solutions to data mining-related problems;
* JDM essentials—concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects;
* JDM in practice—the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API.
* Free, downloadable KJDM source code referenced in the book available here
* Data mining introduction—an overview of data mining and the problems it can address across industries; JDM's place in strategic solutions to data mining-related problems;
* JDM essentials—concepts, design approach and design issues, with detailed code examples in Java; a Web Services interface to enable JDM functionality in an SOA environment; and illustration of JDM XML Schema for JDM objects;
* JDM in practice—the use of JDM from vendor implementations and approaches to customer applications, integration, and usage; impact of data mining on IT infrastructure; a how-to guide for building applications that use the JDM API.
* Free, downloadable KJDM source code referenced in the book available here