Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
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 | ||
| ||
Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors
| Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | X, 339 p. : ill. ; 24 cm |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
00A69 - General applied mathematics [MSC 2020] 62-XX - Statistics [MSC 2020] 62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 62P30 - Applications of statistics in engineering and industry; control charts [MSC 2020] |
| Soggetto non controllato |
Copulas
Forecasting High-dimensional statistics Multiscale processes Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113607 |
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors
| Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors |
| Pubbl/distr/stampa | [Cham], : Springer, 2015 |
| Descrizione fisica | X, 339 p. : ill. ; 24 cm |
| Soggetto topico |
00A69 - General applied mathematics [MSC 2020]
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020] 62-XX - Statistics [MSC 2020] 62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 62P30 - Applications of statistics in engineering and industry; control charts [MSC 2020] |
| Soggetto non controllato |
Copulas
Forecasting High-dimensional statistics Multiscale processes Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00113607 |
| [Cham], : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors
| Modeling and stochastic learning for forecasting in high dimensions / Anestis Antoniadis, Jean-Michel Poggi, Xavier Brossat editors |
| Edizione | [[Cham] : Springer, 2015] |
| Pubbl/distr/stampa | X, 339 p., : ill. ; 24 cm |
| Descrizione fisica | Pubblicazione in formato elettronico |
| Soggetto topico |
00B25 - Proceedings of conferences of miscellaneous specific interest [MSC 2020]
00A69 - General applied mathematics [MSC 2020] 62-XX - Statistics [MSC 2020] 62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 62P30 - Applications of statistics in engineering and industry; control charts [MSC 2020] |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-SUN0113607 |
| X, 339 p., : ill. ; 24 cm | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Random Forests with R / Robin Genuer, Jean-Michel Poggi
| Random Forests with R / Robin Genuer, Jean-Michel Poggi |
| Autore | Genuer, Robin |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | x, 98 p. : ill. ; 24 cm |
| Altri autori (Persone) | Poggi, Jean-Michel |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] |
| Soggetto non controllato |
Classification
Data analysis Decision Trees High-Dimensional Data Interpretable Methods Machine learning Nearest neighbor R packages Random forests Regression Supervised Methods Variable Importance Variable Selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249700 |
Genuer, Robin
|
||
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Random Forests with R / Robin Genuer, Jean-Michel Poggi
| Random Forests with R / Robin Genuer, Jean-Michel Poggi |
| Autore | Genuer, Robin |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | x, 98 p. : ill. ; 24 cm |
| Altri autori (Persone) | Poggi, Jean-Michel |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] |
| Soggetto non controllato |
Classification
Data analysis Decision Trees High-Dimensional Data Interpretable Methods Machine learning Nearest neighbor R packages Random forests Regression Supervised Methods Variable Importance Variable Selection |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00249700 |
|
Genuer, Robin
|
||
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||