Semi Supervised Learning With Partially Labeled Examples

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Semi Supervised Learning With Partially Labeled Examples

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Author : Nam Hoang Nguyen
language : en
Publisher:
Release Date : 2010

Semi Supervised Learning With Partially Labeled Examples written by Nam Hoang Nguyen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Traditionally, machine learning community has been focused on supervised learning where the source of learning is fully labeled examples including both input features and corresponding output labels. As one way to alleviate the costly effort of collecting fully labeled examples, semi-supervised learning usually concentrates on utilizing a large amount of unlabeled examples together with a relatively small number of fully labeled examples to build better classifiers. Even though many semi-supervised learning algorithms are able to take advantage of unlabeled examples, there is a significant amount of effort in designing good models, features, kernels, and similarity functions. In this dissertation, we focus on semi-supervised learning with partially labeled examples. Partially labeled data can be viewed as a trade-off between fully labeled data and unlabeled data, which can provide additional discriminative information in comparison to unlabeled data and requires less human effort to collect than fully labeled data. In our setting of semi-supervised learning with partially labeled examples, the learning method is provided with a large amount of partially labeled examples and is usually augmented with a relatively small set of fully labeled examples. Our main goal is to integrate partially labeled examples into the conventional learning framework, i.e. to build a more accurate classifier. The dissertation addresses four different semi-supervised learning problems in presence of partially labeled examples. In addition, we summarize general principles for the semi-supervised learning with partially labeled examples.

Learning With Partially Labeled And Interdependent Data

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Author : Massih-Reza Amini
language : en
Publisher: Springer
Release Date : 2015-05-07

Learning With Partially Labeled And Interdependent Data written by Massih-Reza Amini and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-07 with Computers categories.

This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data. It reveals new applications, primarily web related, that transgress the classical machine learning framework through learning with interdependent data. The book traces how the semi-supervised paradigm and the learning to rank paradigm emerged from new web applications, leading to a massive production of heterogeneous textual data. It explains how semi-supervised learning techniques are widely used, but only allow a limited analysis of the information content and thus do not meet the demands of many web-related tasks. Later chapters deal with the development of learning methods for ranking entities in a large collection with respect to precise information needed. In some cases, learning a ranking function can be reduced to learning a classification function over the pairs of examples. The book proves that this task can be efficiently tackled in a new framework: learning with interdependent data. Researchers and professionals in machine learning will find these new perspectives and solutions valuable. Learning with Partially Labeled and Interdependent Data is also useful for advanced-level students of computer science, particularly those focused on statistics and learning.

Some Contributions To Semi Supervised Learning

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Author : Paven Kumar Mallapragada
language : en
Publisher:
Release Date : 2010

Some Contributions To Semi Supervised Learning written by Paven Kumar Mallapragada and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Cluster analysis categories.

Semi Supervised Learning With Side Information

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Author : Yi Liu
language : en
Publisher:
Release Date : 2007

Semi Supervised Learning With Side Information written by Yi Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computer science categories.

Ijcai 03

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Author : International Joint Conferences on Artificial Intelligence
language : en
Publisher:
Release Date : 2003

Ijcai 03 written by International Joint Conferences on Artificial Intelligence and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.

Enhancement To Selective Incremental Approach For Transductive Nearest Neighbour Classification

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Author : E. Madhusudhana Reddy
language : en
Publisher: GRIN Verlag
Release Date : 2012-12-28

Enhancement To Selective Incremental Approach For Transductive Nearest Neighbour Classification written by E. Madhusudhana Reddy and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-28 with Education categories.

Master's Thesis from the year 2012 in the subject Didactics - Computer Science, , course: COMPUTER SCIENCE & ENGINEERING, language: English, abstract: During the last years, semi-supervised learning has emerged as an exciting new direction in machine learning research. It is closely related to profound issues of how to do inference from data, as witnessed by its overlap with transductive inference. Semi-Supervised learning is the half-way between Supervised and Unsupervised Learning. In this majority of the patterns are unlabelled, they are present in Test set and knowed labeled patterns are present in Training set. Using these training set, we assign the labels for test set. Here our Proposed method is using Nearest Neighbour Classifier for Semi-Supervised learning we can label the unlabelled patterns using the labeled patterns and then compare these method with the traditionally Existing methods as graph mincut, spectral graph partisan, ID3,Nearest Neighbour Classifier and we are going to prove our Proposed method is more scalable than the Existing methods and reduce time complexity of SITNNC(Selective Incremental Approach for Transductive Nearest Neighbour Classifier) using Leaders Algorithm.

Proceedings Of The Seventh Siam International Conference On Data Mining

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Author : Chid Apte
language : en
Publisher: Society for Industrial and Applied Mathematics (SIAM)
Release Date : 2007

Proceedings Of The Seventh Siam International Conference On Data Mining written by Chid Apte and has been published by Society for Industrial and Applied Mathematics (SIAM) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Computers categories.

The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.

Encyclopedia Of Data Warehousing And Mining

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Author : John Wang
language : en
Publisher:
Release Date : 2008

Encyclopedia Of Data Warehousing And Mining written by John Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Data mining categories.

Ijcai

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Author :
language : en
Publisher:
Release Date : 2007

Ijcai written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Artificial intelligence categories.

Boosting And Online Learning For Classification And Ranking

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Author : Hamed Valizadegan
language : en
Publisher:
Release Date : 2010

Boosting And Online Learning For Classification And Ranking written by Hamed Valizadegan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Automatic classification categories.