Reversing uncertainty sampling to improve active learning schemes

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Active learning provides promising methods to optimize the cost of manually annotating a dataset. However, practitioners in many areas do not massively resort to such methods because they present technical difficulties and do not provide a guarantee of good performance, especially in skewed distribu...

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Detalles Bibliográficos
Autores principales: Cardellino, Cristian, Alonso i Alemany, Laura
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2015
Materias:
Ciencias Informáticas
active learning
pool-based uncertainty sampling
Aprendizaje
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/52131
http://44jaiio.sadio.org.ar/sites/default/files/asai184-191.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata

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