Publicação
An ordinal data method for the classification with reject option
| Resumo: | In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluation. This article motivates and presents a novel method to learn the reject region on complex data. Observations are replicated and then a single binary classifier determines the decision plane. The proposed method is an extension of a method available in the literature for the classification of ordinal data. Our method is compared with standard techniques on synthetic and real datasets, emphasizing the advantages of the proposed approach. |
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| Autores principais: | Ricardo Sousa |
| Outros Autores: | Beatriz Mora; Jaime S Cardoso |
| Assunto: | Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
| Ano: | 2009 |
| País: | Portugal |
| Tipo de documento: | livro |
| Tipo de acesso: | acesso restrito |
| Instituição associada: | Universidade do Porto |
| Idioma: | inglês |
| Origem: | Repositório Aberto da Universidade do Porto |
| Resumo: | In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluation. This article motivates and presents a novel method to learn the reject region on complex data. Observations are replicated and then a single binary classifier determines the decision plane. The proposed method is an extension of a method available in the literature for the classification of ordinal data. Our method is compared with standard techniques on synthetic and real datasets, emphasizing the advantages of the proposed approach. |
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