On the I-Type Error for the Probabilistic–Combinatorial Formal (VKF) Learning Method

For a specially designed training sample, it is necessary to generate a set of hypotheses larger than r = (m – 1)/8ε, so the probabilistic–combinatorial formal (VKF) learning method has the I-type error lesser than ε on m test cases.

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Publication Details

Journal
Automatic Documentation and Mathematical Linguistics
Published
2025-12-01
DOI
https://doi.org/10.3103/s0005105525701110
Primary Topic
Machine Learning and Algorithms
Type
article
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article

On the I-Type Error for the Probabilistic–Combinatorial Formal (VKF) Learning Method

D. V. Vinogradov
Automatic Documentation and Mathematical Linguistics
Machine Learning and Algorithms
article

On the I-Type Error for the Probabilistic–Combinatorial Formal (VKF) Learning Method

D. V. Vinogradov
article en

Abstract

For a specially designed training sample, it is necessary to generate a set of hypotheses larger than r = (m – 1)/8ε, so the probabilistic–combinatorial formal (VKF) learning method has the I-type error lesser than ε on m test cases.

Automatic Documentation and Mathematical LinguisticsVol. 59(6)
Russian Academy of Sciences (RU)
Quality Education
Openalex Percentile: Top 15%
Machine Learning and Algorithms
DOISourceOpenAlex
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