Building classification trees using the total uncertainty criterion
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Publication:149051
DOI10.1002/int.10143zbMath1101.68799OpenAlexW2143074819MaRDI QIDQ149051
Serafín Moral, Joaquín Abellán, Serafín Moral, Joaquín Abellán
Publication date: December 2003
Published in: International Journal of Intelligent Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/int.10143
Related Items (17)
Classification with decision trees from a nonparametric predictive inference perspective ⋮ Equivalence relations among dominance concepts on probability intervals and general credal sets ⋮ Evaluating credal classifiers by utility-discounted predictive accuracy ⋮ An introduction to the imprecise Dirichlet model for multinomial data ⋮ Using credal C4.5 for calibrated label ranking in multi-label classification ⋮ Credal sets representable by reachable probability intervals and belief functions ⋮ A two-step anomaly detection based method for PU classification in imbalanced data sets ⋮ A new robust classifier on noise domains: bagging of Credal C4.5 trees ⋮ Maximising entropy on the nonparametric predictive inference model for multinomial data ⋮ Split Criterions for Variable Selection Using Decision Trees ⋮ Combining Decision Trees Based on Imprecise Probabilities and Uncertainty Measures ⋮ Requirements for total uncertainty measures in Dempster–Shafer theory of evidence ⋮ Supervised classification using probabilistic decision graphs ⋮ Measures of divergence on credal sets ⋮ imptree ⋮ A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds ⋮ Uncertainty measures on probability intervals from the imprecise Dirichlet model
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