Statistical Data Mining and Knowledge Discovery
Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approache
1128483517
Statistical Data Mining and Knowledge Discovery
Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approache
58.95 In Stock
Statistical Data Mining and Knowledge Discovery

Statistical Data Mining and Knowledge Discovery

by Hamparsum Bozdogan (Editor)
Statistical Data Mining and Knowledge Discovery

Statistical Data Mining and Knowledge Discovery

by Hamparsum Bozdogan (Editor)

eBook

$58.95 

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Overview

Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approache

Product Details

ISBN-13: 9781135441012
Publisher: CRC Press
Publication date: 07/29/2003
Sold by: Barnes & Noble
Format: eBook
Pages: 624
File size: 15 MB
Note: This product may take a few minutes to download.

About the Author

Hamparsum Bozdogan

Table of Contents

The Role of Bayesian and Frequentist Multivariate Modeling in Statistical Data Mining. Intelligent Statistical Data Mining with Information Complexity and Genetic Algorithms. Econometric and Statistical Data Mining, Prediction and Policy-Making. Data Mining Strategies for the Detection of Chemical Warfare Agents. Disclosure Limitation for Large Contingency Tables. Partial Membership Models with Application to Disability Survey Data. Automated Scoring of Polygraph Data. Missing Value Algorithms in Decision Trees. Unsupervised Learning from Incomplete Data Using a Mixture Model Approach. Improving the Performance of Radial Basis Function (RBF). Use of Kernel Based Techniques for Sensor Validation in Nuclear Power Plants. Data Mining and Traditional Regression. An Extended Sliced Inverse Regression. Using Genetic Programming to Improve the Group Method of Data Handling. Data Mining for Monitoring Plant Devices Using GMDH and Pattern Classification. Statistical Modeling and Data Mining to Identify the Consumer Preferences. Testing for Structural Change Over Time of Brand Attribute Perceptions. Kernel PCA for Feature Extraction with Information Complexity. Global Principal Component Analysis for Dimensionality Reduction in Distributed Data Mining. A New Metric for Categorical Data. Ordinal Logistic Modeling Using ICOMP as a Goodness-of-Fit Criterion. Comparing Latent Class Factor Analysis with the Traditional Approach in Data Mining. On Cluster Effects in Mining Complex Econometric Data. Neural Networks Based Data Mining Techniques For Steel Making. Solving Data Clustering Problem as a String Search Problem. Behavior-Based Recommender Systems as Value-Added Services for Scientific Libraries. GTP (General Text Parser) Software for Text Mining. Implication Intensity: From the Basic Statistical Definition to the Entropic Version. Use of a Secondary Splitting Criterion in Classification Forest Construction. A Method Integrating Self-Organizing Maps to Predict the Probability of Barrier Removal. Cluster Analysis of Imputed Financial Data Using an Augmentation-Based Algorithm. Data Mining in Federal Agencies. STING: Evaluation of Scientific & Technological Innovation and Progress. The Semantic Conference Organizer.

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