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5 Undernutrition in Sub‐Saharan Africa: A Critical Assessment of the Evidence

Peter Svedberg

in The Political Economy of Hunger: Volume 3: Endemic Hunger

Published in print:
1991
Published Online:
January 2008
ISBN:
9780198286370
eISBN:
9780191718441
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198286370.003.0006
Subject:
Economics and Finance, Development, Growth, and Environmental

From 5% to 45% of the population of sub-Saharan Africa appear to be undernourished, depending on the indicator and sources consulted. This enormous discrepancy calls for a diagnosis of the extent of ... More


Outlier Robust Prediction

Raymond L. Chambers and Robert G. Clark

in An Introduction to Model-Based Survey Sampling with Applications

Published in print:
2012
Published Online:
May 2012
ISBN:
9780198566625
eISBN:
9780191738449
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198566625.003.0010
Subject:
Mathematics, Probability / Statistics

Outlier robust prediction describes methods for estimating the population total when the sample contains representative outliers, i.e. true values that are extremely unlikely under the working model, ... More


Geometry of Covariate Shift with Applications to Active Learning

Kanamori Takafumi and Shimodaira Hidetoshi

in Dataset Shift in Machine Learning

Published in print:
2008
Published Online:
August 2013
ISBN:
9780262170055
eISBN:
9780262255103
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262170055.003.0006
Subject:
Computer Science, Machine Learning

This chapter examines learning algorithms under the covariate shift in which training and test data are drawn from different distributions. Using a naive estimator under the covariate shift, such as ... More


Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers

Cozman Fabio and Cohen Ira

in Semi-Supervised Learning

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262033589
eISBN:
9780262255899
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262033589.003.0004
Subject:
Computer Science, Machine Learning

This chapter presents a number of conclusions. Firstly, labeled and unlabeled data contribute to a reduction in variance in semi-supervised learning under maximum-likelihood estimation. Secondly, ... More


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