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W6-1 Neural Networks for Data Mining Learning Objectives Understand the concept and different types of artificial neural networks (ANN) Learn the advantages and limitations of ANN Understand how backpropagation neural networks learn Understand the complete process of using neural networks Appreciate the wide variety of applications of neural networks N eural networks have emerged as advanced data mining tools in cases where other techniques may not produce satisfactory predictive models. As the term implies, neural networks have a biologically inspired modeling capability, but are essentially statistical modeling tools. In this chapter, we study the basics of neural network model- ing, some specific applications, and the process of implementing a neural network project. 6.1 Opening Vignette: Using Neural Networks to Predict Beer Flavors with Chemical Analysis 6.2 Basic Concepts of Neural Networks 6.3 Learning in Artificial Neural Networks (ANN) 6.4 Developing Neural Network–Based Systems 6.5 A Sample Neural Network Project 6.6 Other Neural Network Paradigms 6.7 Applications of Artificial Neural Networks 6.8 A Neural Network Software Demonstration ONLINE CHAPTER 6 6.1 OPENING VIGNETTE: USING NEURAL NETWORKS TO PREDICT BEER FLAVORS WITH CHEMICAL ANALYSIS Coors Brewers Ltd., based in Burton-upon-Trent, Britain’s brewing capital, is proud of having the United Kingdom’s top beer brands, a 20 percent share of the market, years of experience, and of the best people in the business. Popular brands include Carling (the country’s best-selling lager), Grolsch, Coors Fine Light Beer, Sol, and Korenwolf.
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W6-2 Business Intelligence: A Managerial Approach PROBLEM Today’s customer is confronted with variety of options regarding what he or she drinks. A drinker’s choice depends on various factors, such as mood, venue, and occasion.The goal of Coors is to ensure that the customer chooses a Coors brand every time. According to Coors,creativity is the key to being successful in the long term.To be the customer’s choice brand, Coors needs to be creative and anticipative about the customer’s ever-changing moods.An important issue with beers is the flavor; each beer has a distinc- tive flavor. These flavors are mostly determined through panel tests. However, such tests take time. If Coors could understand the beer flavor based solely on its chemical compo- sition,it would open up new avenues to create beer that would suit customer expectations. The relationship between chemical analysis and beer flavor is not clearly understood yet. Substantial data exists about its chemical composition and sensory analysis. Coors needed a mechanism to link those two together. Neural networks were applied to create the link between chemical composition and sensory analysis.
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This note was uploaded on 04/29/2012 for the course CSCI 5600 taught by Professor Liang during the Fall '12 term at CUHK.

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