Knowledge-Based Clustering
Chapter One
Clustering and Fuzzy Clustering
This chapter provides a comprehensive, focused introduction to clustering, viewed
as a fundamental means of exploratory data analysis, unsupervised learning, data
granulation, and information compression. We discuss the underlying principles,
elaborate on the basic taxonomy of numerous clustering algorithms (including
such essential classes as hierarchical, objective function-based algorithms),
and review the main interpretation mechanisms associated with various clustering
algorithms.
1.1. INTRODUCTION
Making sense of data is an ongoing task of researchers and professionals in
almost every practical endeavor. The age of information technology, characterized
by a vast array of data, has enormously amplified this quest and made it
even more challenging. Data collection anytime and everywhere has become the
reality of our lives. Understanding the data, revealing underlying phenomena,
and visualizing major tendencies are major undertakings pursued in intelligent
data analysis (IDA), data mining (DM), and system modelin ... read full excerpt from Knowledge-Based Clustering: From Data to Information Granules ebook
