On Issues of Instance Selection
Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms
Advances in Instance Selection for Instance-Based Learning Algorithms
Likelihood-Based Data Squashing: A Modeling Approach to Instance Construction
A Unifying View on Instance Selection
Web Mining
Discovery of Web Robot Sessions Based on their Navigational Patterns
Using Site Semantics to Analyze, Visualize, and Support Navigation
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Cubegrades: Generalizing Association Rules
Support Vector Machines and the Bayes Rule in Classification
Automated Remote Sensing with Near Infrared Reflectance Spectra: Carbonate Recognition
Techniques of Cluster Algorithms in Data Mining
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
Discretization: An Enabling Technique