Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/32055
Autoria: | Ferreira, A. S. Marques, A. |
Editor: | Theodore Chadjipadelis Berthold Lausen Angelos Markos Tae Rim Lee Angela Montanari Rebecca Nugent |
Data: | 2021 |
Título próprio: | Performance measures in discrete supervised classification |
Título e volume do livro: | Data analysis and rationality in a complex world: IFCS 2019 |
Paginação: | 47 - 56 |
Referência bibliográfica: | Ferreira, A. S., & Marques, A. (2021). Performance measures in discrete supervised classification. In: T. Chadjipadelis, B. Lausen, A. Markos, T. R. Lee, A. Montanari, & R. Nugent (Eds.). Data Analysis and Rationality in a Complex World: IFCS 2019. (Studies in classification, data analysis, and knowledge organization (pp. 47-56). Springer. https://doi.org/10.1007/978-3-030-60104-1_6 |
ISBN: | 978-3-030-60103-4 |
DOI (Digital Object Identifier): | 10.1007/978-3-030-60104-1_6 |
Palavras-chave: | Balanced classes Performance measures Separability of classes Supervised classification |
Resumo: | The evaluation of results in Cluster Analysis frequently appears in the literature, and a variety of evaluation measures have been proposed. On the contrary, in supervised classification, particularly in the discrete case, the subject of results’ evaluation is relatively scarce in this field of the literature. This is the motto underlying this study. The evaluation of the performance of any model of supervised classification is, generally, based on the number of cases correctly or incorrectly predicted by the model. However, these measures can lead to a misleading evaluation when the data is not balanced. More recently, other types of measures have been studied as association or agreement coefficients, the Huberty index, Mutual information, and even ROC curves. Exploratory studies were conducted in this study to understand the relationship between each measure and data characteristics, namely, sample size, balance, and separability of classes. To this end, simulated data and a Beta regression model in the performance of the models were used. |
Arbitragem científica: | yes |
Acesso: | Acesso Aberto |
Aparece nas coleções: | BRU-CRI - Comunicações a conferências internacionais |
Ficheiros deste registo:
Ficheiro | Tamanho | Formato | |
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conferenceObject_97542.pdf | 160,81 kB | Adobe PDF | Ver/Abrir |
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