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Boosting : foundations and algorithms / / Robert E. Schapire and Yoav Freund
| Boosting : foundations and algorithms / / Robert E. Schapire and Yoav Freund |
| Autore | Schapire Robert E. |
| Pubbl/distr/stampa | Cambridge, Massachusetts : , : MIT Press, , c2012 |
| Descrizione fisica | 1 online resource (544 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | FreundYoav |
| Collana | Adaptive computation and machine learning series |
| Soggetto topico |
Boosting (Algorithms)
Supervised learning (Machine learning) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-67835-6
9786613655288 0-262-30118-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foundations of machine learning -- Using AdaBoost to minimize training error -- Direct bounds on the generalization error -- The margins explanation for boosting's effectiveness -- Game theory, online learning, and boosting -- Loss minimization and generalizations of boosting -- Boosting, convex optimization, and information geometry -- Using confidence-rated weak predictions -- Multiclass classification problems -- Learning to rank -- Attaining the best possible accuracy -- Optimally efficient boosting -- Boosting in continuous time. |
| Record Nr. | UNINA-9910260629203321 |
Schapire Robert E.
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| Cambridge, Massachusetts : , : MIT Press, , c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Boosting : foundations and algorithms / / Robert E. Schapire and Yoav Freund
| Boosting : foundations and algorithms / / Robert E. Schapire and Yoav Freund |
| Autore | Schapire Robert E. |
| Pubbl/distr/stampa | Cambridge, : The MIT Press, 2012 |
| Descrizione fisica | 1 online resource (544 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | FreundYoav |
| Collana | Adaptive computation and machine learning series |
| Soggetto topico |
Boosting (Algorithms)
Supervised learning (Machine learning) |
| Soggetto non controllato |
Artificial intelligence
Algorithms and data structures |
| ISBN |
0-262-30039-7
1-280-67835-6 9786613655288 0-262-30118-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Foundations of machine learning -- Using AdaBoost to minimize training error -- Direct bounds on the generalization error -- The margins explanation for boosting's effectiveness -- Game theory, online learning, and boosting -- Loss minimization and generalizations of boosting -- Boosting, convex optimization, and information geometry -- Using confidence-rated weak predictions -- Multiclass classification problems -- Learning to rank -- Attaining the best possible accuracy -- Optimally efficient boosting -- Boosting in continuous time. |
| Record Nr. | UNINA-9910529509803321 |
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Schapire Robert E.
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| Cambridge, : The MIT Press, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Continual semi-supervised learning : first International Workshop, CSSL 2021, Virtual event, August 19-20, 2021, Revised selected papers / / edited by Fabio Cuzzolin, Kevin Cannons, and Vincenzo Lomonaco
| Continual semi-supervised learning : first International Workshop, CSSL 2021, Virtual event, August 19-20, 2021, Revised selected papers / / edited by Fabio Cuzzolin, Kevin Cannons, and Vincenzo Lomonaco |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (148 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN | 3-031-17587-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996490356303316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Continual semi-supervised learning : first International Workshop, CSSL 2021, Virtual event, August 19-20, 2021, Revised selected papers / / edited by Fabio Cuzzolin, Kevin Cannons, and Vincenzo Lomonaco
| Continual semi-supervised learning : first International Workshop, CSSL 2021, Virtual event, August 19-20, 2021, Revised selected papers / / edited by Fabio Cuzzolin, Kevin Cannons, and Vincenzo Lomonaco |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (148 pages) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN | 3-031-17587-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910616207403321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
| Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, ©2006 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) |
ChapelleOlivier
SchölkopfBernhard ZienAlexander |
| Collana | Adaptive computation and machine learning |
| Soggetto topico | Supervised learning (Machine learning) |
| Soggetto non controllato | COMPUTER SCIENCE/Machine Learning & Neural Networks |
| ISBN |
1-282-09618-4
0-262-25589-8 1-4294-1408-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - Introduction to Semi-Supervised Learning; 2 - A Taxonomy for Semi-Supervised Learning Methods; 3 - Semi-Supervised Text Classification Using EM; 4 - Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 - Probabilistic Semi-Supervised Clustering with Constraints; 6 - Transductive Support Vector Machines; 7 - Semi-Supervised Learning Using Semi- Definite Programming; 8 - Gaussian Processes and the Null-Category Noise Model; 9 - Entropy Regularization; 10 - Data-Dependent Regularization
11 - Label Propagation and Quadratic Criterion12 - The Geometric Basis of Semi-Supervised Learning; 13 - Discrete Regularization; 14 - Semi-Supervised Learning with Conditional Harmonic Mixing; 15 - Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 - Modifying Distances; 18 - Large-Scale Algorithms; 19 - Semi-Supervised Protein Classification Using Cluster Kernels; 20 - Prediction of Protein Function from Networks; 21 - Analysis of Benchmarks; 22 - An Augmented PAC Model for Semi- Supervised Learning 23 - Metric-Based Approaches for Semi- Supervised Regression and Classification24 - Transductive Inference and Semi-Supervised Learning; 25 - A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index |
| Record Nr. | UNINA-9910777620503321 |
| Cambridge, Mass., : MIT Press, ©2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Sch?olkopf, Alexander Zien
| Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Sch?olkopf, Alexander Zien |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, c2006 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) |
ChapelleOlivier
Sch?olkopfBernhard ZienAlexander |
| Collana | Adaptive computation and machine learning |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN |
1-282-09618-4
0-262-25589-8 1-4294-1408-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - Introduction to Semi-Supervised Learning; 2 - A Taxonomy for Semi-Supervised Learning Methods; 3 - Semi-Supervised Text Classification Using EM; 4 - Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 - Probabilistic Semi-Supervised Clustering with Constraints; 6 - Transductive Support Vector Machines; 7 - Semi-Supervised Learning Using Semi- Definite Programming; 8 - Gaussian Processes and the Null-Category Noise Model; 9 - Entropy Regularization; 10 - Data-Dependent Regularization
11 - Label Propagation and Quadratic Criterion12 - The Geometric Basis of Semi-Supervised Learning; 13 - Discrete Regularization; 14 - Semi-Supervised Learning with Conditional Harmonic Mixing; 15 - Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 - Modifying Distances; 18 - Large-Scale Algorithms; 19 - Semi-Supervised Protein Classification Using Cluster Kernels; 20 - Prediction of Protein Function from Networks; 21 - Analysis of Benchmarks; 22 - An Augmented PAC Model for Semi- Supervised Learning 23 - Metric-Based Approaches for Semi- Supervised Regression and Classification24 - Transductive Inference and Semi-Supervised Learning; 25 - A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index |
| Record Nr. | UNINA-9910809030503321 |
| Cambridge, Mass., : MIT Press, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Supervised learning with complex-valued neural networks / / Sundaram Suresh, Narasimhan Sundararajan, and Ramasamy Savitha
| Supervised learning with complex-valued neural networks / / Sundaram Suresh, Narasimhan Sundararajan, and Ramasamy Savitha |
| Autore | Suresh Sundaram |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Heidelberg ; ; New York, : Springer, c2013 |
| Descrizione fisica | 1 online resource (XXII, 170 p.) |
| Disciplina | 006.31 |
| Altri autori (Persone) |
SundararajanNarasimhan
SavithaRamasamy |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Supervised learning (Machine learning)
Neural networks (Computer science) |
| ISBN | 3-642-29491-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Fully Complex-valued Multi Layer Perceptron Networks -- Fully Complex-valued Radial Basis Function Networks -- Performance Study on Complex-valued Function Approximation Problems -- Circular Complex-valued Extreme Learning Machine Classifier -- Performance Study on Real-valued Classification Problems -- Complex-valued Self-regulatory Resource Allocation Network -- Conclusions and Scope for FutureWorks (CSRAN). |
| Record Nr. | UNINA-9910437919903321 |
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Suresh Sundaram
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| Heidelberg ; ; New York, : Springer, c2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Supervised machine learning : optimization framework and applications with SAS and R / / Tanya Kolosova and Samuel Berestizhevsky
| Supervised machine learning : optimization framework and applications with SAS and R / / Tanya Kolosova and Samuel Berestizhevsky |
| Autore | Kolosova Tanya |
| Pubbl/distr/stampa | Boca Raton, Florida ; ; London ; ; New York : , : CRC Press, , [2021] |
| Descrizione fisica | 1 online resource (xxiv, 160 pages) |
| Disciplina | 006.31 |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN |
0-429-29759-9
1-000-17681-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910794383403321 |
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Kolosova Tanya
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| Boca Raton, Florida ; ; London ; ; New York : , : CRC Press, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Supervised machine learning : optimization framework and applications with SAS and R / / Tanya Kolosova and Samuel Berestizhevsky
| Supervised machine learning : optimization framework and applications with SAS and R / / Tanya Kolosova and Samuel Berestizhevsky |
| Autore | Kolosova Tanya |
| Pubbl/distr/stampa | Boca Raton, Florida ; ; London ; ; New York : , : CRC Press, , [2021] |
| Descrizione fisica | 1 online resource (xxiv, 160 pages) |
| Disciplina | 006.31 |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN |
0-429-29759-9
1-000-17681-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910816356303321 |
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Kolosova Tanya
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| Boca Raton, Florida ; ; London ; ; New York : , : CRC Press, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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