Introduction to Semi-Supervised Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning)
Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Get and download textbook Introduction to Semi-Supervised Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning) for free
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Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data is unlabeled, or in the supervised paradigm (e.g., classification, regression) where all the data is labeled.The goal of semi-supervised learning is to understand how combining labeled and unlabeled data may change the learning behavior, and design algorithms that take advantage of such a combination. Semi-supervised learning is of great interest in machine learning and data mining because it can use readily available unlabeled data Introduction to Semi-Supervised Learning new edition
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Introduction to semi-supervised learning: Andrew B. Goldberg, Ronald Brachman, Thomas Dietterich, Xiaojin Zhu
Morgan Claypool 9781598295474 Introduction to Semi-Supervised Learning Description Semi-supervised learning is a learning paradigm concerned with the study of how computers and natural systems such as humans learn in the presence of both labeled and unlabeled data. Traditionally, learning has been studied either in the unsupervised paradigm (eg, clustering, outlier detection) where all the data are unlabeled, or in the supervised paradigm (eg, classification, regression) where all the data
Introduction to Semi-Supervised Learning (Synthesis Lectures on Artificial Intelligence and Machine Learning), ISBN-13: 9781598295474, ISBN-10: 1598295470
author andrew b goldberg author xiaoxian zhu format paperback language english publication year 29 02 2008 series synthesis lectures on artificial intelligence and machine learning subject social sciences subject 2 education teaching title introduction to semi supervised learning author zhu xiaojin goldberg andrew brachman ronald editor dietterich thomas editor publisher morgan claypool publication date sep 15 2009 pages 100 binding paperback dimensions 7 50 wx 9 25 hx 0 30 d isbn 1598295470 s
Introduction to Semi-Supervised Learning Textbook
Traditionally, learning has been studied either in the unsupervised paradigm (e.g., clustering, outlier detection) where all the data is unlabeled, or in the supervised paradigm (e.g
Semi-supervised learning is of great interest in machine learning and data mining because it can use readily available unlabeled data
