Revisiting the optimal probability estimator from small samples for data mining

DOI10.2478/amcs-2019-0058zbMath1430.62023OpenAlexW2999031338WikidataQ126387189 ScholiaQ126387189MaRDI QIDQ2299201

Bojan Cestnik

Publication date: 20 February 2020

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2478/amcs-2019-0058

zbMATH Keywords

minimal errorprobability estimationsmall samples\(m\)-estimate

Mathematics Subject Classification ID

Bayesian problems; characterization of Bayes procedures (62C10) Foundations and philosophical topics in statistics (62A01) Research exposition (monographs, survey articles) pertaining to statistics (62-02) Sequential statistical analysis (62L10)

Uses Software

• R
• scmamp

Cites Work

• Rare-event probability estimation with conditional Monte Carlo
• Statistical decision theory and Bayesian analysis. 2nd ed
• Realistic quantum probability
• On the optimality of the simple Bayesian classifier under zero-one loss
• ROC `n' rule learning -- towards a better understanding of covering algorithms
• On the smoothing of multinomial estimates using Liouville mixture models and applications
• Machine Learning
• Common Errors in Statistics (And How to Avoid Them)
• Optimal estimator of hypothesis probability for data mining problems with small samples
• The Manual of Strategic Economic Decision Making
• Probability for Statistics and Machine Learning
• An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules
• How to Estimate Probabilities
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