Item response theory as a feature selection and interpretation tool in the context of machine learning.
Optimizing the number and utility of features to use in a classification analysis has been the subject of many research studies. Most current models use end-classifications as part of the feature reduction process, leading to circularity in the methodology. The approach demonstrated in the present r...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 59; no. 2; pp. 471 - 483 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Feb2021
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| Acceso en línea: | Ver este registro en EBSCOhost |