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Marketing research class lectures_204963144-Data-Mining-in-Market-Research

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Data Mining in Market Research • What is data mining? – Methods for finding interesting structure in large databases • E.g. patterns, prediction rules, unusual cases – Focus on efficient, scalable algorithms • Contrasts with emphasis on correct inference in statistics – Related to data warehousing, machine learning • Why is data mining important? – Well marketed; now a large industry; pays well – Handles large databases directly – Can make data analysis more accessible to end users • Semi-automation of analysis • Results can be easier to interpret than e.g. regression models • Strong focus on decisions and their implementation CRISP-DM Process Model Data Mining Software • Many providers of data mining software – SAS Enterprise Miner, SPSS Clementine, Statistica Data Miner, MS SQL Server, Polyanalyst, KnowledgeSTUDIO, … – See http://www.kdnuggets.com/software/suites.html for a list – Good algorithms important, but also need good facilities for handling data and meta-data • We’ll use: – WEKA (Waikato Environment for Knowledge Analysis) • Free (GPLed) Java package with GUI • Online at www.cs.waikato.ac.nz/ml/weka • Witten and Frank, 2000. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. – R packages • E.g. rpart, class, tree, nnet, cclust, deal, GeneSOM, knnTree, mlbench, randomForest, subselect Data Mining Terms • Different names for familiar statistical concepts, from databa ...
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