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Overview
Clear and concise explanations to understand the learning paradigms.
Chapters written by leading world experts.
Synopsis
This book presents research on some of the most recent advances in data mining and knowledge discovery, providing theory as well as its applications on practical real world applications. The methodologies discussed encompass tools like Bayesian networks, and major facets of computational intelligence paradigms.
Contributions from top class researchers include:
- Recent trends in data mining and knowledge discovery
- Advanced data mining techniques in semi-conductor manufacturing
- Clustering and visualization in retail markets baskets
- Segmentation of continuous data
- Instance selection using evolutionary algorithms
- Cooperative co-evolution for data mining of Bayesian networks
- Knowledge discovery and data mining in medicine
- Satellite image classification
- Knowledge discovery using rough sets
This book presents both practical detail and some of the most up-to-date theory in the field, useful for postgraduates and those who wish to develop applications using advanced data mining and knowledge discovery techniques.