Fontanella, Francesco
(2006)
An Approach to Pattern Recognition by Evolutionary Computation.
[Tesi di dottorato]
(Inedito)
| Tipologia del documento: |
Tesi di dottorato
|
| Lingua: |
English |
| Titolo: |
An Approach to Pattern Recognition by Evolutionary Computation |
| Autori: |
| Autore | Email |
|---|
| Fontanella, Francesco | [non definito] |
|
| Data: |
2006 |
| Tipo di data: |
Pubblicazione |
| Numero di pagine: |
165 |
| Istituzione: |
Università degli Studi di Napoli Federico II |
| Dipartimento: |
Informatica e sistemistica |
| Dottorato: |
Ingegneria informatica ed automatica |
| Ciclo di dottorato: |
18 |
| Coordinatore del Corso di dottorato: |
| nome | email |
|---|
| Cordella, Luigi Pietro | [non definito] |
|
| Tutor: |
| nome | email |
|---|
| Cordella, Luigi | [non definito] |
|
| Data: |
2006 |
| Numero di pagine: |
165 |
| Parole chiave: |
Evolutionary Computation, Pattern Recognition, Prototype Generation |
| Settori scientifico-disciplinari del MIUR: |
Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni |
[error in script]
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| Depositato il: |
31 Lug 2008 |
| Ultima modifica: |
04 Dic 2014 08:10 |
| URI: |
http://www.fedoa.unina.it/id/eprint/576 |
| DOI: |
10.6092/UNINA/FEDOA/576 |
Abstract
Evolutionary Computation has been inspired by the natural phenomena of evolution. It provides a quite general heuristic, exploiting few basic concepts: reproduction of individuals, variation phenomena that affect the likelihood of survival of individuals, inheritance of parents features by offspring. EC has been widely used in the last years to effectively solve hard, non linear and very complex problems.
Among the others, EC–based algorithms have also been used to tackle
classification problems. Classification is a process according to which an object is attributed to one of a finite set of classes or, in other words, it is recognized as belonging to a set of equal or similar entities, identified by a label. Most likely, the main aspect of classification concerns the generation of prototypes to be used to recognize unknown patterns. The role of prototypes is that of representing patterns belonging to the different classes defined within a given problem. For most of the problems of practical interest, the generation of such prototypes is a very hard problem, since a prototype must be able to represent patterns belonging to the same class, which may be significantly dissimilar each other. They must also be able to discriminate patterns belonging to classes different from the one that they represent. Moreover, a prototype should contain the minimum amount of information required to satisfy the requirements just mentioned. The research presented in this thesis, has led to the definition of an EC–based framework to be used for prototype generation. The defined framework does not provide for the use of any particular kind of prototypes. In fact, it can generate any kind of prototype once an encoding scheme for the used prototypes has been defined. The generality of the framework can be exploited to develop many applications. The framework has been employed to implement two specific applications for prototype generation.
The developed applications have been tested on several data sets and the results compared with those obtained by other approaches previously presented in the literature.
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