Information Technology Reference
In-Depth Information
Chapter 1
Feature Selection for Data and Pattern
Recognition: An Introduction
Urszula Sta nczyk and Lakhmi C. Jain
Abstract
Surrounded by data and information in various forms we need to
characterise and describe objects of our universe using some attributes of nominal or
numerical type. Selection of features can be performed basing on domain knowledge,
executed through dedicated approaches, driven by some particular inherent proper-
ties of methodologies and techniques employed, or governed by other factors or rules.
This chapter presents a general and brief introduction to topics of feature selection
for data and pattern recognition. Its main aim is to provide short descriptions of the
chapters included in this volume.
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Keywords
Feature
Feature selection
Pattern recognition
Data mining
1.1 Introduction
Some say that our earliest memories form when, as children, we learn to describe
the world we live in, and express verbally what we feel and think, how we perceive
other people, objects, events, abstract concepts. While we grow older, we learn to
detect and recognise patterns [
20
], and our discriminating skills grow as well. We
develop associations, preferences and dislikes, which are employed, consciously and
subconsciously, when choices are made, actions taken.
Imagine opening an unknown thick topic and finding in it a whole page dedicated
to a line of thought of some character, jumping from one topic to another, along with
connecting ideas, feelings and memories, digressions. Without looking at the cover
or the title page, by similarity to a stream of consciousness, one instantly thinks
