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[null,"1.","Record Nr.",null,"UNINA9910777620503321"]
[null,null,"Titolo",null,"Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien"]
[null,null,"Pubbl/distr/stampa",null,"Cambridge, Mass., : MIT Press, ©2006"]
[null,null,"ISBN",null,"1-282-09618-4"]
[{"$nulls":4},"0-262-25589-8"]
[{"$nulls":4},"1-4294-1408-1"]
[null,null,"Descrizione fisica",null,"1 online resource (528 p.)"]
[null,null,"Collana",null,"Adaptive computation and machine learning"]
[null,null,"Disciplina",null,"006.3/1"]
[null,null,"Soggetti",null,"Supervised learning (Machine learning)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [479]-497)."]
[null,null,"Nota di contenuto",null,"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"]
[{"$nulls":4},"11 - Label Propagation and Quadratic Criterion12 - The Geometric Basis of Semi-Supervised Learning; 13 - Discrete Regularization; 14 - Semi-Supervised Learning with Conditional Harmonic Mixing; 15 - Graph Kernels by Spectral Transforms; 16-  Spectral Methods for Dimensionality Reduction; 17 - Modifying Distances; 18 - Large-Scale Algorithms; 19 - Semi-Supervised Protein Classification Using Cluster Kernels; 20 - Prediction of Protein Function from Networks; 21 - Analysis of Benchmarks; 22 - An Augmented PAC Model for Semi- Supervised Learning"]
[{"$nulls":4},"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"]
[null,null,null,"Sommario/riassunto","A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at "]
[{"$nulls":4},"state-of-the-art algorithms, applications benchmark experiments, and directions for future research."]