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2012 | 22 | 3 | 629-645

Tytuł artykułu

Optimal estimator of hypothesis probability for data mining problems with small samples

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The paper presents a new (to the best of the authors' knowledge) estimator of probability called the "Epₕ√2 completeness estimator" along with a theoretical derivation of its optimality. The estimator is especially suitable for a small number of sample items, which is the feature of many real problems characterized by data insufficiency. The control parameter of the estimator is not assumed in an a priori, subjective way, but was determined on the basis of an optimization criterion (the least absolute errors).The estimator was compared with the universally used frequency estimator of probability and with Cestnik's m-estimator with respect to accuracy. The comparison was realized both theoretically and experimentally. The results show the superiority of the Epₕ√2 completeness estimator over the frequency estimator for the probability interval pₕ ∈ (0.1, 0.9). The frequency estimator is better for pₕ ∈ [0, 0.1] and pₕ ∈ [0.9, 1].








Opis fizyczny




  • Faculty of Computer Science, West Pomeranian University of Technology, Żołnierska 49, 71-210 Szczecin, Poland
  • Institute of Quantitative Methods, Maritime University of Szczecin, Wały Chrobrego 1-2, 70-500 Szczecin, Poland


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