Principles of Data Mining

• Main Author: Bramer, Max (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: London : Springer London, 2007.
• Subjects: Computer science.; Computer programming.; Data structures (Computer science).; Computers.; Database management.; Information storage and retrieval.; Artificial intelligence.; Computer Science.; Data Structures, Cryptology and Information Theory.; Theory of Computation.; Information Storage and Retrieval.; Database Management.; Artificial Intelligence (incl. Robotics).; Programming Techniques.

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and...

Table of Contents:

• Data for Data Mining
• to Classification: Na¨ive Bayes and Nearest Neighbour
• Using Decision Trees for Classification
• Decision Tree Induction: Using Entropy for Attribute Selection
• Decision Tree Induction: Using Frequency Tables for Attribute Selection
• Estimating the Predictive Accuracy of a Classifier
• Continuous Attributes
• Avoiding Overfitting of Decision Trees
• More About Entropy
• Inducing Modular Rules for Classification
• Measuring the Performance of a Classifier
• Association Rule Mining I
• Association Rule Mining II
• Clustering
• Text Mining.