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

Full Product Details

Author:   Kenneth D. Lawrence (New Jersey Institute of Technology, Newark, USA) ,  Stephan Kudyba (New Jersey Institute of Technology, Newark, USA) ,  Ronald K. Klimberg (Saint Joseph's University, Philadelphia, Pennsylvania, USA) ,  Stephan Kudyba
Publisher:   Taylor & Francis Ltd
Imprint:   Auerbach
Weight:   0.780kg
ISBN:  

9780849385223

ISBN 10:   0849385229
Pages:   332
Publication Date:   22 December 2007
Audience:   College/higher education ,  Tertiary & Higher Education ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

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

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

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