Blocked 3×2 Cross-Validated t-Test for Comparing Supervised Classification Learning Algorithms

DOI10.1162/NECO_a_00532zbMath1418.62261WikidataQ45958540 ScholiaQ45958540MaRDI QIDQ5378319

Li Jihong, Jia Huichen, Wang Ruibo, Wang Yu

Publication date: 12 June 2019

Published in: Neural Computation (Search for Journal in Brave)

zbMATH Keywords

classificationanalysis of variancemachine learning algorithmsblocked \(3\times 2\) cross-validation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Statistical block designs (62K10) Analysis of variance and covariance (ANOVA) (62J10)

Related Items (3)

Block-regularized repeated learning-testing for estimating generalization error ⋮ Credible Intervals for Precision and Recall Based on aK-Fold Cross-Validated Beta Distribution ⋮ Block-Regularized m × 2 Cross-Validated Estimator of the Generalization Error

Cites Work

• Classifier variability: accounting for training and testing
• Inference for the generalization error
• Automatic Labeling of Semantic Roles on Chinese FrameNet
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