Ebook: Principles of Data Mining

Principles of Data Mining; About This Book; Contents; 1. Introduction to Data Mining; 1.1 The Data Explosion; 1.2 Knowledge Discovery; 1.3 Applications of Data Mining; 1.4 Labelled and Unlabelled Data; 1.5 Supervised Learning: Classification; 1.6 Supervised Learning: Numerical Prediction; 1.7 Unsupervised Learning: Association Rules; 1.8 Unsupervised Learning: Clustering; 2. Data for Data Mining; 2.1 Standard Formulation; 2.2 Types of Variable; 2.2.1 Categorical and Continuous Attributes; 2.3 Data Preparation; 2.3.1 Data Cleaning; 2.4 Missing Values; 2.4.1 Discard Instances.;Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. Principles of Data Mining explains and explores the principal techniques of Data Mining: for classification, association rule mining and clustering. Each topic is clearly explained and illustrated by detailed worked examples, with a focus on algorithms rather than mathematical formalism. It is written for readers without a strong background in mathematics or statistics, and any formulae used are explained in detail. This secon.