Distributed Bayesian machine learning procedures
Saved in:
| Date: | 2019 |
|---|---|
| Main Author: | B. A. Beletskij |
| Format: | Article |
| Language: | English |
| Published: |
2019
|
| Series: | Cybernetics and Systems Analysis |
| Online Access: | http://jnas.nbuv.gov.ua/article/UJRN-0000986324 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Journal Title: | Library portal of National Academy of Sciences of Ukraine | LibNAS |
Institution
Library portal of National Academy of Sciences of Ukraine | LibNASSimilar Items
Distributed bayesian procedures of the text information recognition
by: B. A. Beletskij, et al.
Published: (2018)
by: B. A. Beletskij, et al.
Published: (2018)
Bayesian procedures of recognition of hematology diseases
by: A. M. Gupal, et al.
Published: (2017)
by: A. M. Gupal, et al.
Published: (2017)
Bayesian procedures of recognition of inflammatory processes in brain gliomas
by: Ja. Gridina, et al.
Published: (2017)
by: Ja. Gridina, et al.
Published: (2017)
Using the bayesian recognition procedures for analysis of the influence of channel blockers in brain gliomas
by: Ja Gridina, et al.
Published: (2015)
by: Ja Gridina, et al.
Published: (2015)
Artificial Intelligence, Machine Learning, and Intelligent Decision Support Systems: Iterative "Learning" SQG-based procedures for Distributed Models' Linkage
by: T. Ermolieva, et al.
Published: (2022)
by: T. Ermolieva, et al.
Published: (2022)
Analysis of protein structures of blood plasma in gliomas using Bayesian recognition procedures on the markov chain model
by: A. M. Hupal, et al.
Published: (2022)
by: A. M. Hupal, et al.
Published: (2022)
Machine learning methods for environmental monitoring
by: P. V. Mikava, et al.
Published: (2024)
by: P. V. Mikava, et al.
Published: (2024)
Bayesian recognition procedures in the analysis of blood plasma protein structures according to laser spectrograph measurements in brain tumors
by: A. M. Hupal, et al.
Published: (2022)
by: A. M. Hupal, et al.
Published: (2022)
Modification of the Use of Bayesian Recognition Procedures for Inflammatory Processes in Gliomas, Metastasis and Meningiomas by Indicators of Erythrocyte Sedimentation Rate
by: A. L. Tarasov, et al.
Published: (2021)
by: A. L. Tarasov, et al.
Published: (2021)
Analysis of Surface Plasmon Resonance Indicators Using Bayesian Recognition Procedures with Independent Signs in Gliomas, Metastases and Meningiomas
by: A. L. Tarasov
Published: (2021)
by: A. L. Tarasov
Published: (2021)
Bayesian Recognition Procedures with Independent Signs of Inflammatory Processes in Gliomas, Metastases and Meningiomas by Indicators of Erythrocyte Sedimentation Rate
by: A. L. Tarasov
Published: (2021)
by: A. L. Tarasov
Published: (2021)
Face recognition based on machine learning algorithms
by: N. B. Shakhovska, et al.
Published: (2017)
by: N. B. Shakhovska, et al.
Published: (2017)
Analysis of neurosurgical pathologies using bayesian recognition procedures for indicators of surface plasmon resonance in the aggregation of blood cells
by: Ja. Gridina, et al.
Published: (2020)
by: Ja. Gridina, et al.
Published: (2020)
Horizontal and vertical scalability of machine learning methods
by: B. O. Biletskyi
Published: (2019)
by: B. O. Biletskyi
Published: (2019)
Horizontal and Vertical Scalability of Machine Learning Methods
by: Biletskyy, B.O.
Published: (2019)
by: Biletskyy, B.O.
Published: (2019)
Application of machine learning in software engineering: an overview
by: O. G. Moroz, et al.
Published: (2019)
by: O. G. Moroz, et al.
Published: (2019)
Using machine learning methods in practice
by: Ya. O. Tupalo
Published: (2018)
by: Ya. O. Tupalo
Published: (2018)
Who is a subject in machine learning?
by: V. M. Loktiev
Published: (2024)
by: V. M. Loktiev
Published: (2024)
ALMA: Machine learning breastfeeding chatbot
by: K. Achtaich, et al.
Published: (2023)
by: K. Achtaich, et al.
Published: (2023)
Application of machine learning in software engineering: an overview
by: Moroz, O.H., et al.
Published: (2019)
by: Moroz, O.H., et al.
Published: (2019)
Minimax deviation strategies for machine learning and recognition with short learning samples
by: M. I. Schlesinger, et al.
Published: (2022)
by: M. I. Schlesinger, et al.
Published: (2022)
Bayesian statistics in human genetics
by: L. A. Atramentova
Published: (2020)
by: L. A. Atramentova
Published: (2020)
IMPLEMENTING OF MICROSOFT AZURE MACHINE LEARNING TECHNOLOGY FOR ELECTRIC MACHINES OPTIMIZATION
by: Pliugin, V. E., et al.
Published: (2019)
by: Pliugin, V. E., et al.
Published: (2019)
Metalearning as One of the Task of the Machine Learning Problems
by: Savchenko, Ye.A., et al.
Published: (2019)
by: Savchenko, Ye.A., et al.
Published: (2019)
Metalearning as One of the Task of the Machine Learning Problems
by: Ye. A. Savchenko, et al.
Published: (2019)
by: Ye. A. Savchenko, et al.
Published: (2019)
Machine Learning algorithms in Big Data context
by: V. M. Tereshchenko, et al.
Published: (2018)
by: V. M. Tereshchenko, et al.
Published: (2018)
The image oversampling using means of machine learning
by: R. O. Tkachenko, et al.
Published: (2016)
by: R. O. Tkachenko, et al.
Published: (2016)
The Principles of Application of Machine Learning in Classification of Network Traffic
by: Ya. M. Antonyuk, et al.
Published: (2018)
by: Ya. M. Antonyuk, et al.
Published: (2018)
Logical Puzzles Solving Based on Machine Learning
by: S. I. Shapovalova, et al.
Published: (2019)
by: S. I. Shapovalova, et al.
Published: (2019)
Analysis of fundus images based on machine learning
by: O. V. Karas, et al.
Published: (2024)
by: O. V. Karas, et al.
Published: (2024)
Machine learning in lung lesion detection caused by certain diseases
by: D. Khoroshchuk, et al.
Published: (2023)
by: D. Khoroshchuk, et al.
Published: (2023)
Some Frameworks for Big Data Analytics and Machine Learning
by: A. A. Ursatev
Published: (2016)
by: A. A. Ursatev
Published: (2016)
English Accent Recognition Using Deep Machine Learning
by: A. V. Manokhin, et al.
Published: (2021)
by: A. V. Manokhin, et al.
Published: (2021)
Progress in Determination of Protein Spatial Structure Based on Machine Learning
by: B. O. Biletskyi
Published: (2021)
by: B. O. Biletskyi
Published: (2021)
About One Machine Learning Method For Paraphrase Identification
by: O. O. Marchenko, et al.
Published: (2016)
by: O. O. Marchenko, et al.
Published: (2016)
Machine learning methods analysis in the document classification problem
by: A. P. Zhyrkova, et al.
Published: (2020)
by: A. P. Zhyrkova, et al.
Published: (2020)
Machine learning methods analysis in the document classification problem
by: Zhyrkova, A.P., et al.
Published: (2021)
by: Zhyrkova, A.P., et al.
Published: (2021)
Using Machine Learning Methods to Estimate the Cost of Housing
by: V. V. Tretynyk, et al.
Published: (2021)
by: V. V. Tretynyk, et al.
Published: (2021)
Application of machine learning to improving numerical weather prediction
by: Yu. Doroshenko, et al.
Published: (2020)
by: Yu. Doroshenko, et al.
Published: (2020)
Diabetes prediction using an improved machine learning approach
by: S. Lyaqini, et al.
Published: (2021)
by: S. Lyaqini, et al.
Published: (2021)
Similar Items
-
Distributed bayesian procedures of the text information recognition
by: B. A. Beletskij, et al.
Published: (2018) -
Bayesian procedures of recognition of hematology diseases
by: A. M. Gupal, et al.
Published: (2017) -
Bayesian procedures of recognition of inflammatory processes in brain gliomas
by: Ja. Gridina, et al.
Published: (2017) -
Using the bayesian recognition procedures for analysis of the influence of channel blockers in brain gliomas
by: Ja Gridina, et al.
Published: (2015) -
Artificial Intelligence, Machine Learning, and Intelligent Decision Support Systems: Iterative "Learning" SQG-based procedures for Distributed Models' Linkage
by: T. Ermolieva, et al.
Published: (2022)