Data Mining Methods and Applications / Edition 1

by Kenneth D. Lawrence, Stephan Kudyba, Ronald K. Klimberg

Overview

With today’s information explosion, many organizations are now able to access a wealth of valuable data. Unfortunately, most of these organizations find they are ill-equipped to organize this information, let alone put it to work for them.

Gain a Competitive Advantage

• Employ data mining in research and forecasting
• Build models with data management tools and methodology optimization
• Gain sophisticated breakdowns and complex analysis through multivariate, evolutionary, and neural net methods
• Learn how to classify data and maintain quality

Transform Data into Business Acumen

Data Mining Methods and Applications supplies organizations with the data management tools that will allow them to harness the critical facts and figures needed to improve their bottom line. Drawing from finance, marketing, economics, science, and healthcare, this forward thinking volume:

• Demonstrates how the transformation of data into business intelligence is an essential aspect of strategic decision-making
• Emphasizes the use of data mining concepts in real-world'scenarios with large database components
• Focuses on data mining and forecasting methods in conducting market research

Product Details

ISBN-13:	9780849385223
Publisher:	Taylor & Francis
Publication date:	12/22/2007
Series:	Discrete Mathematics and Its Applications Series
Pages:	332
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Kenneth D. Lawrence, Stephan Kudyba, Ronald K. Klimberg

Table of Contents

TECHNIQUES OF DATA MINING
An Approach to Analyzing and Modeling Systems for Real-Time Decisions
Ensemble Strategies for Neural Network Classifiers
Neural Network Classification with Uneven Misclassification
Costs and Imbalanced Group Sizes
Data Cleansing with Independent Component Analysis
A Multiple Criteria Approach to Creating Good Teams over Time
APPLICATIONS OF DATA MINING
Data Mining Applications in Higher Education
Data Mining for Market Segmentation with Market Share Data
A Case Study Approach
An Enhancement of the Pocket Algorithm with Ratche for Use in Data Mining Applications
Identification and Prediction of Chronic Conditions for Health Plan Members Using Data Mining Techniques
Monitoring and Managing Data and Process Quality
Using Data Mining: Business Process Management for the Purchasing and Accounts Payable Processes
Data Mining for Individual Consumer Models and Personalized
Retail Promotions
OTHER AREAS OF DATA MINING
Data Mining Common Definitions, Applications,
and Misunderstandings
Fuzzy Sets in Data Mining and Ordinal Classification
Developing an Associative Keyword Space of the Data Mining
Literature through Latent Semantic Analysis
A Classification Model for a Two-Class (New Product Purchase)
Discrimination Process using Multiple-Criteria
Linear Programming
Index