Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing

Progress in predictive machine learning is typically measured on the basis of performance comparisons on benchmark datasets. Traditionally these kinds of empirical evaluation are carried out on large numbers of datasets, but this is becoming increasingly hard due to computational requirements and th...

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Autores principales:	Song, Hao, Flach, Peter
Formato:	Artículo
Lenguaje:	inglés
Publicado:	2021
Materias:	Item Response Theory Adaptive Testing Model Evaluation Benchmarks
Acceso en línea:	https://dialnet.unirioja.es/servlet/oaiart?codigo=9032586
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