Statistical Data Modeling and Machine Learning with Applications II
The present reprint contains all of the articles in the second edition of the Special Issue titled “Statistical Data Modeling and Machine Learning with Applications II”. This Special Issue belongs to the “Mathematics and Computer Science” Section and aims to publish research on the theory and applic...
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| Materialtyp: | Online |
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| Språk: | engelska |
| Utgiven: |
MDPI - Multidisciplinary Digital Publishing Institute
2023
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| Ämnen: | |
| Länkar: | ONIX_20230808_9783036582009_11 |
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| _version_ | 1869524683805687808 |
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| collection | Directory of Open Access Books |
| description | The present reprint contains all of the articles in the second edition of the Special Issue titled “Statistical Data Modeling and Machine Learning with Applications II”. This Special Issue belongs to the “Mathematics and Computer Science” Section and aims to publish research on the theory and application of statistical data modeling and machine learning. New mathematical methods and approaches, new algorithms and research frameworks, and their applications aimed at solving diverse and nontrivial practical problems are proposed and developed in this SI. We believe that the chosen papers are attractive and useful to the international scientific community and will contribute to further research in the field of statistical data modeling and machine learning. |
| format | Online |
| id | doab-20.500.12854ir-112505 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1125052024-03-30T12:51:26Z Statistical Data Modeling and Machine Learning with Applications II Gocheva-Ilieva, Snezhana Ivanov, Atanas Kulina, Hristina forecasting model electricity energy consumption grey model artificial neural network machine learning rotation CART ensemble bagging boosting arcing simplified selective ensemble linear stacked model IoV xNN K-MEANS anomaly detection single-index models composite quantile regression SCAD Laplace error penalty (LEP) causality Bayesian networks scalability group lasso penalty data integration network estimation stability selection time series model wavelet transform neural network NARX ionospheric parameters gambling jackpot multidimensional integrals Monte Carlo methods lattice sequences digital sequences surface approximation surface segmentation surface denoising gaussian process latent variable model line geometry line elements regression classification prediction meteorological parameters traffic incidents multi-agent architecture air pollution random forest ARIMA errors MIMO averaging strategy multi-step ahead prediction unmeasured forecast Explainableartificial intelligence credit card frauds deep learning long short-term memory fraud classification lung cancer tumor CT image one-stage detector YOLO multi-scale receptive field data analysis decision trees LightGBM SHAP leisure time influencing factors time allocation neural networks cosmic rays space weather n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science The present reprint contains all of the articles in the second edition of the Special Issue titled “Statistical Data Modeling and Machine Learning with Applications II”. This Special Issue belongs to the “Mathematics and Computer Science” Section and aims to publish research on the theory and application of statistical data modeling and machine learning. New mathematical methods and approaches, new algorithms and research frameworks, and their applications aimed at solving diverse and nontrivial practical problems are proposed and developed in this SI. We believe that the chosen papers are attractive and useful to the international scientific community and will contribute to further research in the field of statistical data modeling and machine learning. 2023-08-08T15:23:41Z 2023-08-08T15:23:41Z 2023 book ONIX_20230808_9783036582009_11 9783036582009 9783036582016 https://directory.doabooks.org/handle/20.500.12854/112505 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/7622 https://mdpi.com/books/pdfview/book/7622 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-8201-6 10.3390/books978-3-0365-8201-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036582009 9783036582016 344 Basel open access |
| spellingShingle | forecasting model electricity energy consumption grey model artificial neural network machine learning rotation CART ensemble bagging boosting arcing simplified selective ensemble linear stacked model IoV xNN K-MEANS anomaly detection single-index models composite quantile regression SCAD Laplace error penalty (LEP) causality Bayesian networks scalability group lasso penalty data integration network estimation stability selection time series model wavelet transform neural network NARX ionospheric parameters gambling jackpot multidimensional integrals Monte Carlo methods lattice sequences digital sequences surface approximation surface segmentation surface denoising gaussian process latent variable model line geometry line elements regression classification prediction meteorological parameters traffic incidents multi-agent architecture air pollution random forest ARIMA errors MIMO averaging strategy multi-step ahead prediction unmeasured forecast Explainableartificial intelligence credit card frauds deep learning long short-term memory fraud classification lung cancer tumor CT image one-stage detector YOLO multi-scale receptive field data analysis decision trees LightGBM SHAP leisure time influencing factors time allocation neural networks cosmic rays space weather n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science Statistical Data Modeling and Machine Learning with Applications II |
| title | Statistical Data Modeling and Machine Learning with Applications II |
| title_full | Statistical Data Modeling and Machine Learning with Applications II |
| title_fullStr | Statistical Data Modeling and Machine Learning with Applications II |
| title_full_unstemmed | Statistical Data Modeling and Machine Learning with Applications II |
| title_short | Statistical Data Modeling and Machine Learning with Applications II |
| title_sort | statistical data modeling and machine learning with applications ii |
| topic | forecasting model electricity energy consumption grey model artificial neural network machine learning rotation CART ensemble bagging boosting arcing simplified selective ensemble linear stacked model IoV xNN K-MEANS anomaly detection single-index models composite quantile regression SCAD Laplace error penalty (LEP) causality Bayesian networks scalability group lasso penalty data integration network estimation stability selection time series model wavelet transform neural network NARX ionospheric parameters gambling jackpot multidimensional integrals Monte Carlo methods lattice sequences digital sequences surface approximation surface segmentation surface denoising gaussian process latent variable model line geometry line elements regression classification prediction meteorological parameters traffic incidents multi-agent architecture air pollution random forest ARIMA errors MIMO averaging strategy multi-step ahead prediction unmeasured forecast Explainableartificial intelligence credit card frauds deep learning long short-term memory fraud classification lung cancer tumor CT image one-stage detector YOLO multi-scale receptive field data analysis decision trees LightGBM SHAP leisure time influencing factors time allocation neural networks cosmic rays space weather n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | forecasting model electricity energy consumption grey model artificial neural network machine learning rotation CART ensemble bagging boosting arcing simplified selective ensemble linear stacked model IoV xNN K-MEANS anomaly detection single-index models composite quantile regression SCAD Laplace error penalty (LEP) causality Bayesian networks scalability group lasso penalty data integration network estimation stability selection time series model wavelet transform neural network NARX ionospheric parameters gambling jackpot multidimensional integrals Monte Carlo methods lattice sequences digital sequences surface approximation surface segmentation surface denoising gaussian process latent variable model line geometry line elements regression classification prediction meteorological parameters traffic incidents multi-agent architecture air pollution random forest ARIMA errors MIMO averaging strategy multi-step ahead prediction unmeasured forecast Explainableartificial intelligence credit card frauds deep learning long short-term memory fraud classification lung cancer tumor CT image one-stage detector YOLO multi-scale receptive field data analysis decision trees LightGBM SHAP leisure time influencing factors time allocation neural networks cosmic rays space weather n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | ONIX_20230808_9783036582009_11 |