OVERFITTING IN MACHINE LEARNING: PROBLEMS AND SOLUTIONS
South Ural State University; V.A. Parasich; I.V. Parasich; South Ural State University; G.I. Volovich; LLC Chelenergopribor; S.G. Nekrasov; South Ural State University; A.V. Parasich; LLC TRIDIVI
- Published
- Publisher
- FSAEIHE South Ural State University (National Research University)
- Journal / collection
- Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics
- Research area
- AI & compute
- Source type
- Journal article
- DOI
- 10.14529/ctcr240202
The original publisher provides the full text and its access options.
Cite this source
South Ural State University; V.A. Parasich; I.V. Parasich; South Ural State University; G.I. Volovich; LLC Chelenergopribor; S.G. Nekrasov; South Ural State University; A.V. Parasich; LLC TRIDIVI. OVERFITTING IN MACHINE LEARNING: PROBLEMS AND SOLUTIONS. Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics. 2024-05. https://doi.org/10.14529/ctcr240202