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Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.]
| Fundamentals of Data Analytics : With a View to Machine Learning / Rudolf Mathar ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 127 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62R07 - Statistical aspects of big data and data science [MSC 2020] 68T05 - Learning and adaptive systems in artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Artificial Intelligence
Classification Clustering Data science Diffusion maps Dimensionality reduction Isomap Kernel methods Machine learning MapReduce Markov decision processes Matrix optimization and approximation Multidimensional Scaling Principal component analysis Spectral clustering Supervised machine learning Support Vector Machines Unsupervised machine learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00249280 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry
| Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry |
| Autore | Vidal, René |
| Pubbl/distr/stampa | New York, : Springer, 2016 |
| Descrizione fisica | XXXII, 566 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ma, Yi
Sastry, S. Shankar |
| Soggetto topico |
14-XX - Algebraic geometry [MSC 2020]
15-XX - Linear and multilinear algebra; matrix theory [MSC 2020] 62B10 - Statistical aspects of information-theoretic topics [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62-XX - Statistics [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 30C10 - Polynomials and rational functions of one complex variable [MSC 2020] 62H35 - Image analysis in multivariate analysis [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 30C40 - Kernel functions in one complex variable and applications [MSC 2020] 14N20 - Configurations and arrangements of linear subspaces [MSC 2020] |
| Soggetto non controllato |
Hybrid system identification
Image and video segmentation Linear subspace models Low-rank matrix theory Manifold learning Principal component analysis Robust principal component analysis Sparse representation theory Spectral clustering Subspace arrangements Subspace clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0114796 |
Vidal, René
|
||
| New York, : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry
| Generalized principal component analysis / René Vidal, Yi Ma, S. Shankar Sastry |
| Autore | Vidal, René |
| Pubbl/distr/stampa | New York, : Springer, 2016 |
| Descrizione fisica | XXXII, 566 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Ma, Yi
Sastry, S. Shankar |
| Soggetto topico |
14-XX - Algebraic geometry [MSC 2020]
14N20 - Configurations and arrangements of linear subspaces [MSC 2020] 15-XX - Linear and multilinear algebra; matrix theory [MSC 2020] 30C10 - Polynomials and rational functions of one complex variable [MSC 2020] 30C40 - Kernel functions in one complex variable and applications [MSC 2020] 62-XX - Statistics [MSC 2020] 62B10 - Statistical aspects of information-theoretic topics [MSC 2020] 62Fxx - Parametric inference [MSC 2020] 62H12 - Estimation in multivariate analysis [MSC 2020] 62H25 - Factor analysis and principal components; correspondence analysis [MSC 2020] 62H35 - Image analysis in multivariate analysis [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62J07 - Ridge regression; shrinkage estimators (Lasso) [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] |
| Soggetto non controllato |
Hybrid system identification
Image and video segmentation Linear subspace models Low-rank matrix theory Manifold learning Principal component analysis Robust principal component analysis Sparse representation theory Spectral clustering Subspace arrangements Subspace clustering |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00114796 |
|
Vidal, René
|
||
| New York, : Springer, 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||