Statistical data mining and knowledge discovery / edited by Hamparsum Bozdogan.

Format:

Book

Contributor:

Bozdogan, H. (Hamparsum), 1945-

Language:

English

Subjects (All):

Data mining--Statistical methods.

Data mining.

Computer algorithms.

Knowledge acquisition (Expert systems).

Physical Description:

588 pages : illustrations ; 25 cm

Place of Publication:

Boca Raton, Fla. : Chapman & Hall/CRC, [2004]

Summary:

This volume brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques.

Contents:

1 The Role of Bayesian and Frequentist Multivariate Modeling in Statistical Data Mining / S. James Press 1

1.2 Is Data Mining Science? 2

1.3 Genesis of Data Mining 3

1.4 The Data Cube and Databases 3

1.5 Structured Query Language 5

1.6 Statistical Problems with Data Mining 6

1.7 Some DM Approaches to Dimension Reduction 7

1.8 Prior Distributions in Data Mining 9

1.9 Some New DM Applications 10

2 Intelligent Statistical Data Mining with Information Complexity and Genetic Algorithms / Hamparsum Bozdogan 15

2.2 What is Information Complexity:ICOMP? 17

2.3 Information Criteria for Multiple Regression Models 31

2.4 A GA for the Regression Modeling 36

2.5 Numerical Examples 41

3 Econometric and Statistical Data Mining, Prediction and Policy-Making / Arnold Zellner 57

3.2 Brief Comments on Scientific Method and Data Mining 59

3.3 The Structural Econometric Modeling, Time Series Analysis (SEMTSA) Approach 61

3.4 Methods Employed in Data Analysis, Modeling and Forecasting 67

3.5 Disaggregation and the Marshallian Macroeconomic Model 71

3.6 A Complete Marshallian Macroeconomic Model 74

4 Data Mining Strategies for the Detection of Chemical Warfare Agents / Jeffrey. L. Solka, Edward J. Wegman, David J. Marchette 79

5 Disclosure Limitation Methods Based on Bounds for Large Contingency Tables With Applications to Disability / Adrian Dobra, Elena A. Erosheva, Stephen E. Fienberg 93

5.2 Example: National Long Term Care Survey Data 95

5.3 Technical Background on Cell Entry Bounds 96

5.4 Decomposable Frontiers 99

5.5 "Greedy" Frontiers 103

5.6 Bounds 108

6 Partial Membership Models with Application to Disability Survey Data / Elena A. Erosheva 117

6.1 Motivation 118

6.2 Functional Disability Data 119

6.3 Full Versus Partial Membership 123

6.4 Bayesian Estimation of the GoM Model 125

6.5 Analysis and Comparison 127

7 Automated Scoring of Polygraph Data / Aleksandra B. Slavkovic 135

7.3 Statistical Models for Classification and Prediction 139

7.4 The Data 141

7.5 Statistical Analysis 144

8 Missing Value Algorithms in Decision Trees / Hyunjoong Kim, Sumer Yates 155

8.2 The Seven Algorithms 156

8.3 The Simulation Study 159

8.4 Results 162

9 Unsupervised Learning from Incomplete Data Using a Mixture Model Approach / Lynette Hunt, Murray Jorgensen 173

9.2 Clustering by Mixture Models 175

9.3 Applications 182

10 Improving the Performance of Radial Basis Function (RBF) Classification Using Information Criteria / Zhenqiu Liu, Hamparsum Bozdogan 193

10.2 Regression Trees 197

10.3 New Kernel Functions 201

10.4 The EM Algorithm 204

10.5 Hybrid Training 208

10.6 Computational Results 210

11 Use of Kernel Based Techniques for Sensor Validation in Nuclear Power Plants / Andrei V. Gribok, Aleksey M. Urmanov, J. Wesley Hines, Robert E. Uhrig 217

11.2 Collinear, Ill-Posed Problems, Regularization 218

11.3 Kernel Regression and MSET 222

11.4 Support Vector Machines 223

11.5 Data Description and Results 225

12 Data Mining and Traditional Regression / Christopher M. Hill, Linda C. Malone, Linda Trocine 233

12.2 Military Manpower Application 234

12.3 Data Mining and Traditional Regression 236

12.4 General Problems 237

12.5 Attempted Solutions 239

12.6 Regression Specific Issues 240

13 An Extended Sliced Inverse Regression / Masahiro Mizuta 251

13.2 Algorithms for SIR Model 252

13.3 Relative Projection Pursuit 254

13.4 SIRrpp 254

14 Using Genetic Programming to Improve the Group Method of Data Handling in Time Series Prediction / M. Hiassat, M.F. Abbod, N. Mort 257

14.2 The Data 258

14.3 Financial Data 259

14.4 Weather Data 259

14.5 Processing of Data 260

14.6 The Group Method of Data Handling (GMDH) 261

14.7 Genetic Programming (GP) 262

14.8 GP-GMDH 263

14.9 Results and Discussion 264

15 Data Mining for Monitoring Plant Devices Using GMDH and Pattern Classification / B.R. Upadhyaya, B. Lu 269

15.2 Description of the Method 273

15.3 Analysis and Results 277

16 Statistical Modeling and Data Mining to Identify Consumer Preferences / Francois Boussu, Jean Jacques Denimal 281

16.2 Data Mining Method 283

16.3 Application to a Textile Data Set 288

17 Testing for Structural Change Over Time of Brand Attribute Perceptions in Market Segments / Sara Dolnicar, Friedrich Leisch 297

17.2 The Managerial Problem 298

17.3 Results from Traditional Analysis 299

17.4 The PBMS and DynPBMS Approaches 300

18 Kernel PCA for Feature Extraction with Information Complexity / Zhenqiu Liu, Hamparsum Bozdogan 309

18.2 Kernel Functions 312

18.3 Kernel PCA 314

18.4 EM for Kernel PCA and On-line PCA 318

18.5 Choosing the Number of Components with Information Complexity 319

18.6 Computational Results 320

19 Global Principal Component Analysis for Dimensionality Reduction in Distributed Data Mining / Hairong Qi, Tse-Wei Wang, J. Douglas Birdwell 323

19.2 Principal Component Analysis 326

19.3 Global PCA for Distributed Homogeneous Databases 327

19.4 Global PCA for Distributed Heterogeneous Databases 330

19.5 Experiments and Results 331

20 A New Metric for Categorical Data / S. H. Al-Harbi, G. P. McKeown, V. J. Rayward-Smith 339

20.2 Dissimilarity Measure 340

20.3 D[subscript CV] Metric 343

20.4 Synthetic Examples 345

20.5 Exploiting the D[subscript CV] Metric 348

21 Ordinal Logistic Modeling Using ICOMP as a Goodness-of-Fit Criterion / J. Michael Lanning, Hamparsum Bozdogan 353

21.2 Model Selection Criteria 356

21.3 Ordinal Logistic Regression 359

21.4 Example Problem: Diabetes Severity 367

22 Comparing Latent Class Factor Analysis with the Traditional Approach in Data Mining / Jay Magidson, Jeroen Vermunt 373

22.2 The Basic LC Factor Model 375

23 On Cluster Effects in Mining Complex Econometric Data / M. Ishaq Bhatti 385

23.2 The Model 387

23.3 An Algorithm for Full Maximum Likelihood Estimation 389

23.4 Application of the Model 392

23.5 Fixed Coefficient Regression Models 394

24 Neural Network-Based Data Mining Techniques for Steel Making / Ravindra K. Sarma, Amar Gupta, Sanjeev Vadhavkar 401

24.2 Productivity from Information Technology (PROFIT) Initiative 403

24.3 Description of Predictive Model 406

24.4 NNRUN

ANN Training Suite 407

24.5 Results and Analysis 409

25 Solving Data Clustering Problem as a String Search Problem / V. Olman, D. Xu, Y. Xu 415

25.2 Mathematical Framework 417

25.3 Stability of MST Structure Under Noise 421

25.4 Statistical Assessment of Identified Clusters 422

25.5 Applications 423

26 Behavior-Based Recommender Systems as Value-Added Services for Scientific Libraries / Andreas Geyer-Schulz, Michael Hahsler, Andreas Neumann, Anke Thede 433

26.2 Recommender Services for Legacy Library Systems 435

26.3 Ehrenberg's Repeat-Buying Theory for Libraries 439

26.4 A Recommender System for the Library of the Universitat Karlsruhe (TH) 448

27 GTP (General Text Parser) Software for Text Mining / Justin T. Giles, Ling Wo, Michael W.

Berry 455

27.2 Model Facilitated by GTP 456

27.3 GTP Usage and Files Generated 457

27.4 Overview of GTP Options 458

27.5 Query Processing with GTPQUERY 464

27.7 Versions of GTP and GTPQUERY 469

27.8 Code Evolution 470

27.9 Future Work 470

28 Implication Intensity: From the Basic Statistical Definition to the Entropic Version / Julien Blanchard, Pascale Kuntz, Fabrice Guillet, Regis Gras 473

28.2 First Definitions 475

28.3 Entropic Version 476

28.4 Experimental Results 478

29 Use of a Secondary Splitting Criterion in Classification Forest Construction / Chang-Yung Yu, Heping Zhang 487

29.2 A Secondary Node-Splitting Criterion 488

29.3 The Formation of a Deterministic Forest 488

29.4 Comparison Data 489

30 A Method Integrating Self-Organizing Maps to Predict the Probability of Barrier Removal / Zhicheng Zhang, Frederic Vanderhaegen 497

30.2 A Method Integrating Self-Organizing Maps Algorithm 498

30.3 Experimental Results 503

31 Cluster Analysis of Imputed Financial Data Using an Augmentation-Based Algorithm / H. Bensmail, R. P. DeGennaro 513

31.2 Data and Preliminary Tests 514

31.3 Clustering and Bayesian Data Augmentation 518

31.4 Bayesian Model Selection for Choosing the Number of Clusters 523

31.5 Analysis of Financial Data 523

32 Data Mining in Federal Agencies / David L. Banks, Robert T. Olszewski 529

32.1 Data Quality 529

32.2 Indexing Data 534

32.3 Screening for Structure with Locally Low Dimension 537

32.4 Estimating Exposure 545

33 STING: Evaluation of Scientific & Technological Innovation and Progress / S. Sirmakessis, K. Markellos, P. Markellou, G. Mayritsakis, K. Perdikouri, A. Tsakalidis, Georgia Panagopoulou 549

33.2 Methodology for the Analysis of Patents 550

33.3 System Description 559

33.4 Technology Indicators 563

34 The Semantic Conference Organizer / Kevin Heinrich, Michael W. Berry, Jack J. Dongarra, Sathish Vadhiyar 571

34.2 Latent Semantic Indexing 572

34.3 Software Issues 573

34.4 Creating a Conference 575

34.5 Future Extensions 579.

Notes:

Includes bibliographical references and index.

ISBN:

1584883448

OCLC:

52134776