Data Mining

Chapter 1 Data Mining and Information Systems: Quo Vadis?

Chapter 2 Response-Based Segmentation Using Finite Mixture Partial Least Squares

Chapter 3 Building Acceptable Classification Models

Chapter 4 Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property

Chapter 5 Classification Techniques and Error Control in Logic Mining

Chapter 6 An Extended Study of the Discriminant Random Forest

Chapter 7 Prediction with the SVM Using Test Point Margins

Chapter 8 Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers

Chapter 9 The Impact of Small Disjuncts on Classifier Learning

Chapter 10 Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile

Chapter 11 PCA-based Time Series Similarity Search

Chapter 12 Evolutionary Optimization of Least-Squares Support Vector Machines

Chapter 13 Genetically Evolved kNN Ensembles

Chapter 14 Behaviorally Founded Recommendation Algorithm for Browsing Assistance Systems

Chapter 15 Using Web Text Mining to Predict Future Events: A Test of the Wisdom of Crowds Hypothesis

Chapter 16 Avoiding Attribute Disclosure with the (Extended) p -Sensitive k -Anonymity Model

Chapter 17 Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data