Data Mining Methods and Applications

by Kenneth D. Lawrence (Editor), Stephan Kudyba (Editor), Ronald K. Klimberg (Editor)

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

Product Details

ISBN-13:	9781040182376
Publisher:	CRC Press
Publication date:	12/22/2007
Sold by:	Barnes & Noble
Format:	eBook
Pages:	336
File size:	5 MB

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