Semi-Supervised Learning with Committees

Name: Semi-Supervised Learning with Committees
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838125701
Price: 430.68 RON
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Exploiting Unlabeled Data using Ensemble Learning Algorithms

Autor: Mohamed Farouk Abdel Hady

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Editura: Sudwestdeutscher Verlag Fur Hochschulschriften AG

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430.68 lei

Supervised learning is a branch of artificial intelligence concerned with developing computer progra...

Informații despre carte

Autor

Mohamed Farouk Abdel Hady

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2011

Pagini

304

EAN

9783838125701

ISBN

3838125703

Enbook ID

06854024

Editura

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Greutate

449

Dimensiuni

152 x 229 x 17

Descriere completă

Supervised learning is a branch of artificial intelligence concerned with developing computer programs that automatically improve with experience through knowledge extraction from examples. Such learning approaches are particularly useful for tasks involving the automatic categorization, retrieval and extraction of knowledge from large collections of data such as text, images and videos. It builds predictive models from labeled data. However, labeling the training data is difficult, expensive, or time consuming, as it requires the effort of human annotators sometimes with specific domain experience. Semi-supervised learning (SSL) aims to minimize the cost of manual annotation by allowing the model to exploit part or all of the available unlabeled data. Semi-supervised learning and ensemble learning are two different paradigms that were developed almost in parallel. Semi-supervised learning tries to improve generalization performance by exploiting unlabeled data, while ensemble learning tries to achieve the same objective by constructing multiple predictors. This book concentrates on SSL with ensembles(committees).

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Semi-Supervised Learning with Committees

Exploiting Unlabeled Data using Ensemble Learning Algorithms

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Descriere completă

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