With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, banking, retail, and many others. Wang and Fu present in detail the state of the art on how to utilize fuzzy neural networks, multilayer perceptron neural networks, radial basis function neural networks, genetic algorithms, and support vector machines in such applications..
Table of Contents: Chapter 1 - Data Exploration as a Process; Chapter 2 - The Nature of the World and Its Impact on Data Preparation; Chapter 3 - Data Preparation as a Process; Chapter 4 - Getting the Data—Basic Preparation; Chapter 5 - Sampling, Variability, and Confidence; Chapter 6 - Handling Nonnumerical Variables; Chapter 7 - Normalizing and Redistributing Variables; Chapter 8 - Replacing Missing and Empty Values; Chapter 9 - Series Variables; Chapter 10 - Preparing the Data Set; Chapter 11 - The Data Survey; Chapter 12 - Using Prepared Data.
Data mining practical machine learning tools and techniques: Second edition
First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches* Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining* Discusses principles and classical algorithms on string matching and their role in data mining
