Classification of ordinal data using neural networks

• Tipo: Artigo em Revista Científica Internacional
• Data: 2005

Autores

da Costa, JP (Autor) FCUP; Cardoso, JS (Autor) FCUP

Indexação

ISI Web of Knowledge - 19 Citações

Scopus - 22 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-000-66W

DOI: 10.1007/11564096_70

Abstract (EN): Many real life problems require the classification of items in naturally ordered classes. These problems are traditionally handled by conventional methods for nominal classes, ignoring the order. This paper introduces a new training model for feedforward neural networks, for multiclass classification problems, where the classes are ordered. The proposed model has just one output unit which takes values in the interval [0,1]; this interval is then subdivided into K subintervals (one for each class), according to a specific probabilistic model. A comparison is made with conventional approaches, as well as with other architectures specific for ordinal data proposed in the literature. The new model compares favourably with the other methods under study, in the synthetic dataset used for evaluation.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8