Nonlinear principal component analysis and its applications / Yuichi Mori, Masahiro Kuroda, Naomichi Makino
| Nonlinear principal component analysis and its applications / Yuichi Mori, Masahiro Kuroda, Naomichi Makino |
| Autore | Mori, Yuichi |
| Pubbl/distr/stampa | [Singapore], : Springer, 2016 |
| Descrizione fisica | X, 80 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Kuroda, Masahiro
Makino, Naomichi |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] |
| Soggetto non controllato |
Alternating Least Squares
Mixed Measurement Level Data Multiple Correspondence Analysis Nonlinear PCA Optimal Scaling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0115078 |
Mori, Yuichi
|
||
| [Singapore], : Springer, 2016 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Nonlinear principal component analysis and its applications / Yuichi Mori, Masahiro Kuroda, Naomichi Makino
| Nonlinear principal component analysis and its applications / Yuichi Mori, Masahiro Kuroda, Naomichi Makino |
| Autore | Mori, Yuichi |
| Pubbl/distr/stampa | [Singapore], : Springer, 2016 |
| Descrizione fisica | X, 80 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Kuroda, Masahiro
Makino, Naomichi |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H30 - Classification and discrimination; cluster analysis (statistical aspects) [MSC 2020] |
| Soggetto non controllato |
Alternating Least Squares
Mixed Measurement Level Data Multiple Correspondence Analysis Nonlinear PCA Optimal Scaling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00115078 |
Mori, Yuichi
|
||
| [Singapore], : Springer, 2016 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||