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Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi editors
| Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | vii, 123 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62P12 - Applications of statistics to environmental and related topics [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62P30 - Applications of statistics in engineering and industry; control charts [MSC 2020] 62P35 - Applications of statistics to physics [MSC 2020] |
| Soggetto non controllato |
Additive Manufacturing Systems
Generalized additive models Interpretability Machine learning Sensitivity |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277671 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi editors
| Interpretability for Industry 4.0 : Statistical and Machine Learning Approaches / Antonio Lepore, Biagio Palumbo, Jean-Michel Poggi editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | vii, 123 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62P12 - Applications of statistics to environmental and related topics [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62P30 - Applications of statistics in engineering and industry; control charts [MSC 2020] 62P35 - Applications of statistics to physics [MSC 2020] |
| Soggetto non controllato |
Additive Manufacturing Systems
Generalized additive models Interpretability Machine learning Sensitivity |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277671 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Mathematics of Public Health : Proceedings of the Seminar on the Mathematical Modelling of COVID-19 / V. Kumar Murty, Jianhong Wu editors
| Mathematics of Public Health : Proceedings of the Seminar on the Mathematical Modelling of COVID-19 / V. Kumar Murty, Jianhong Wu editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | x, 353 p. : ill. ; 24 cm |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
92-XX - Biology and other natural sciences [MSC 2020] 92D30 - Epidemiology [MSC 2020] |
| Soggetto non controllato |
COVID-19 outbreak trajectories
COVID-19 pandemic research Control measures Data modeling Fields math modelling taskforce Forecasting COVID-19 Generalized Linear Models Generalized additive models Intermediate rank spline Link functions Mathematical methods COVID-19 Nearcasting COVID-19 Optimization Plasma treatment COVID-19 Regression analysis Reported and unreported cases SEIR modeling Semi-parametric Models Statistical analysis Transmission dynamics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0277897 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Mathematics of Public Health : Proceedings of the Seminar on the Mathematical Modelling of COVID-19 / V. Kumar Murty, Jianhong Wu editors
| Mathematics of Public Health : Proceedings of the Seminar on the Mathematical Modelling of COVID-19 / V. Kumar Murty, Jianhong Wu editors |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | x, 353 p. : ill. ; 24 cm |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
92-XX - Biology and other natural sciences [MSC 2020] 92D30 - Epidemiology [MSC 2020] |
| Soggetto non controllato |
COVID-19 outbreak trajectories
COVID-19 pandemic research Control measures Data modeling Fields math modelling taskforce Forecasting COVID-19 Generalized Linear Models Generalized additive models Intermediate rank spline Link functions Mathematical methods COVID-19 Nearcasting COVID-19 Optimization Plasma treatment COVID-19 Regression analysis Reported and unreported cases SEIR modeling Semi-parametric Models Statistical analysis Transmission dynamics |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00277897 |
| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Semiparametric Regression with R / Jaroslaw Harezlak, David Ruppert, Matt P. Wand
| Semiparametric Regression with R / Jaroslaw Harezlak, David Ruppert, Matt P. Wand |
| Autore | Harezlak, Jaroslaw |
| Pubbl/distr/stampa | New York, : Springer, 2018 |
| Descrizione fisica | xi, 331 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ruppert, David
Wand, Matt P. |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68N15 - Theory of programming languages [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] |
| Soggetto non controllato |
Bayesian semiparametric regression
Bivariate function extensions Generalized additive models Penalized spines Regression analysis Semiparametric regression analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0125104 |
Harezlak, Jaroslaw
|
||
| New York, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Semiparametric Regression with R / Jaroslaw Harezlak, David Ruppert, Matt P. Wand
| Semiparametric Regression with R / Jaroslaw Harezlak, David Ruppert, Matt P. Wand |
| Autore | Harezlak, Jaroslaw |
| Pubbl/distr/stampa | New York, : Springer, 2018 |
| Descrizione fisica | xi, 331 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ruppert, David
Wand, Matt P. |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62Jxx - Linear inference, regression [MSC 2020] 68N15 - Theory of programming languages [MSC 2020] |
| Soggetto non controllato |
Bayesian semiparametric regression
Bivariate function extensions Generalized additive models Penalized spines Regression analysis Semiparametric regression analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00125104 |
|
Harezlak, Jaroslaw
|
||
| New York, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||