Incluye índice de contenido, referencias bibliográficas, índice alfabético, lista de figuras, lista de tablas

Introduction to data mining.-- What´s it all about?.-- Input: Concepts, instances, and attributes.-- Output: Knowledge representation.-- Algorithms: the basic methods.-- Credibility: Evaluating what´s been learned.-- Advanced data mining.-- Implementations: Real machine learning schemes.-- Data transformations.-- Ensemble learning.-- Moving on: Applications and beyond.-- The weka date mining workbench.-- Introduction to weka.-- The explorer.-- The knowledge flow interface.-- The experimenter.-- The command - line interface.-- Embedded machine learning.-- Writing new learning schemes.-- Tutorial exercises for the weka explorer