Item response theory in AI: analysing machine learning classifiers at the instance level

DOI10.1016/j.artint.2018.09.004zbMath1478.68295OpenAlexW2912981918WikidataQ128465241 ScholiaQ128465241MaRDI QIDQ2321286

Adolfo Martínez-Usó, Ricardo B. C. Prudêncio, José Hernández-Orallo, Fernando Martínez-Plumed

Publication date: 28 August 2019

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2018.09.004

zbMATH Keywords

item response theorymachine learninginstance hardnessartificial intelligence evaluationclassifier metrics

Mathematics Subject Classification ID

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

Related Items (2)

Bayesian inference for multidimensional graded response model using Pólya-Gamma latent variables ⋮ An instance-oriented performance measure for classification

Uses Software

• UCI-ml
• SATzilla
• ltm
• mirt
• OpenML
• IsolationForest

Cites Work

• Selection of relevant features and examples in machine learning
• An instance level analysis of data complexity
• A survey of outlier detection methodologies
• Metalearning
• Algorithm portfolios
• Unnamed Item
• Unnamed Item

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