aiNet: An Artificial Immune Network for Data Analysis

aiNet: An Artificial Immune Network for Data Analysis

Leandro Nunes de Castro (State University of Campinas, Brazil) and Fernando J. Von Zuben (State University of Campinas, Brazil)
Copyright: © 2002 |Pages: 30
DOI: 10.4018/978-1-930708-25-9.ch012
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Abstract

This chapter shows that some of the basic aspects of the natural immune system discussed in the previous chapter can be used to propose a novel artificial immune network model with the main goals of clustering and filtering crude data sets described by high-dimensional samples. Our aim is not to reproduce with confidence any immune phenomenon, but demonstrate that immune concepts can be used as inspiration to develop novel computational tools for data analysis. As important results of our model, the network evolved will be capable of reducing redundancy and describing data structure, including their spatial distribution and cluster interrelations. Clustering is useful in several exploratory pattern analyses, grouping, decision-making and machine-learning tasks, including data mining, knowledge discovery, document retrieval, image segmentation and automatic pattern classification. The data clustering approach was implemented in association with hierarchical clustering and graphtheoretical techniques, and the network performance is illustrated using several benchmark problems. The computational complexity of the algorithm and a detailed sensitivity analysis of the user-defined parameters are presented. A trade-off among the proposed model for data analysis, connectionist models (artificial neural networks) and evolutionary algorithms is also discussed.

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Table of Contents
Acknowledgments
Hussein A. Abbass, Ruhul Sarker, Charles S. Newton
Chapter 1
Vladimir Estivill-Castro, Michael Houle
Distance-based clustering results in optimization problems that typically are NP-hard or NP-complete and for which only approximate solutions are... Sample PDF
Approximating Proximity to Fast and Robust Distance-Based Clustering
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Chapter 2
Erick Cantu-Paz
With computers becoming more pervasive, disks becoming cheaper, and sensors becoming ubiquitous, we are collecting data at an ever-increasing pace.... Sample PDF
On the Use of Evolutionary Algorithms in Data Mining
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Chapter 3
Beatriz de la Iglesia, Victor J. Rayward-Smith
Knowledge Discovery in Databases (KDD) is an iterative and interactive process involving many steps (Debuse, de la Iglesia, Howard & Rayward-Smith... Sample PDF
The Discovery of Interesting Nuggets Using Heuristic Techniques
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Chapter 4
Jay T. Rodstein, Katherine S. Watters
Safety and health issues in virtual offices are part of progressive telecommuting programs. Telecommuting agreements between employers and employees... Sample PDF
From Evolution to Immune to Swarm to? A Simple Introduction to Modern Heuristics
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Chapter 5
Inaki Inza, Pedro Larranaga, Basilio Sierra
Feature Subset Selection (FSS) is a well-known task of Machine Learning, Data Mining, Pattern Recognition or Text Learning paradigms. Genetic... Sample PDF
Estimation of Distribution Algorithms for Feature Subset Selection in Large Dimensionality Domains
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Chapter 6
Jorge Muruzabal
Evolutionary algorithms are by now well-known and appreciated in a number of disciplines including the emerging field of data mining. In the last... Sample PDF
Towards the Cross-Fertilization of Multiple Heuristics: Evolving Teams of Local Bayesian Learners
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Chapter 7
Neil Dunstan, Michael de Raadt
Sensing devices are commonly used for the detection and classification of subsurface objects, particularly for the purpose of eradicating Unexploded... Sample PDF
Evolution of Spatial Data Templates for Object Classification
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Chapter 8
Peter W.H. Smith
Genetic Programming (GP) has increasingly been used as a data-mining tool. For example, it has successfully been used for decision tree induction... Sample PDF
Genetic Programming as a Data-Mining Tool
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Chapter 9
Andries P. Engelbrecht, L. Schoeman, Sonja Rouwhorst
Genetic programming has recently been used successfully to extract knowledge in the form of IF-THEN rules. For these genetic programming approaches... Sample PDF
A Building Block Approach to Genetic Programming for Rule Discovery
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Chapter 10
Rafael S. Parpinelli, Heitor S. Lopes, Alex A. Freitas
This work proposes an algorithm for rule discovery called Ant-Miner (Ant Colony-Based Data Miner). The goal of Ant-Miner is to extract... Sample PDF
An Ant Colony Algorithm for Classification Rule Discovery
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Chapter 11
Jonathan Timmis, Thomas Knight
The immune system is highly distributed, highly adaptive, self-organising in nature, maintains a memory of past encounters and has the ability to... Sample PDF
Artificial Immune Systems: Using the Immune System as Inspiration for Data Mining
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Chapter 12
Leandro Nunes de Castro, Fernando J. Von Zuben
This chapter shows that some of the basic aspects of the natural immune system discussed in the previous chapter can be used to propose a novel... Sample PDF
aiNet: An Artificial Immune Network for Data Analysis
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Chapter 13
Parallel Data Mining  (pages 261-289)
David Taniar, J. Wenny Rahayu
Data mining refers to a process on nontrivial extraction of implicit, previously unknown and potential useful information (such as knowledge rules... Sample PDF
Parallel Data Mining
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