Optimised probabilistic active learning (OPAL)

DOI10.1007/s10994-015-5504-1zbMath1341.68160OpenAlexW586780102MaRDI QIDQ747267

Georg Krempl, Daniel Kottke, Vincent Lemaire

Publication date: 23 October 2015

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-015-5504-1

zbMATH Keywords

active learningerror reductioncost-sensitiveimbalanced datamisclassification lossnon-myopicuncertainty samplingunequal misclassification costs

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

How to measure uncertainty in uncertainty sampling for active learning ⋮ Stream-based active learning for sliding windows under the influence of verification latency ⋮ Evolving multi-label fuzzy classifier ⋮ Toward optimal probabilistic active learning using a Bayesian approach

Uses Software

• UCI-ml
• SMOTE

Cites Work

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• A self-training approach to cost sensitive uncertainty sampling
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• Active Learning
• On the connection coefficients and recurrence relations arising from expansions in series of Laguerre polynomials
• Imbalanced Learning