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Data Mining

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Cover of 'Data Mining'

Table of Contents

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    Book Overview
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    Chapter 1 Data Mining and Information Systems: Quo Vadis?
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    Chapter 2 Response-Based Segmentation Using Finite Mixture Partial Least Squares
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    Chapter 3 Building Acceptable Classification Models
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    Chapter 4 Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property
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    Chapter 5 Classification Techniques and Error Control in Logic Mining
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    Chapter 6 An Extended Study of the Discriminant Random Forest
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    Chapter 7 Prediction with the SVM Using Test Point Margins
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    Chapter 8 Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers
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    Chapter 9 The Impact of Small Disjuncts on Classifier Learning
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    Chapter 10 Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile
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    Chapter 11 PCA-based Time Series Similarity Search
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    Chapter 12 Evolutionary Optimization of Least-Squares Support Vector Machines
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    Chapter 13 Genetically Evolved kNN Ensembles
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    Chapter 14 Behaviorally Founded Recommendation Algorithm for Browsing Assistance Systems
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    Chapter 15 Using Web Text Mining to Predict Future Events: A Test of the Wisdom of Crowds Hypothesis
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    Chapter 16 Avoiding Attribute Disclosure with the (Extended) p -Sensitive k -Anonymity Model
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    Chapter 17 Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data
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