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Bias–variance tradeoff

Known as: Bias–variance dilemma, Bias–variance decomposition, Bias and variance tradeoff 
In statistics and machine learning, the bias–variance tradeoff (or dilemma) is the problem of simultaneously minimizing two sources of error that… Expand
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Related topics

Related topics

24 relations
AlgorithmArtificial neural networkBoosting (machine learning)Bootstrap aggregating
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Broader (3)

Machine learningModel selectionStatistical classification

Papers overview

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Highly Cited
2012
Highly Cited
2012
Understanding the bias-variance tradeoff
 
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Highly Cited
2009
Highly Cited
2009
Exploration-exploitation tradeoff using variance estimates in multi-armed bandits
Algorithms based on upper confidence bounds for balancing exploration and exploitation are gaining popularity since they are easy… Expand
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2007
2007
Bias-variance tradeoff in hybrid generative-discriminative models
Given any generative classifier based on an inexact density model, we can define a discriminative counterpart that reduces its… Expand
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Highly Cited
2004
Highly Cited
2004
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods
Bias-variance analysis provides a tool to study learning algorithms and can be used to properly design ensemble methods well… Expand
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Highly Cited
2002
Highly Cited
2002
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the… Expand
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Highly Cited
2000
Highly Cited
2000
Bias-Variance Error Bounds for Temporal Difference Updates
Temporal difference (td) algorithms are used in reinforcement learning to compute estimates of the value of a given policy in an… Expand
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Highly Cited
1999
Highly Cited
1999
Scale Mixtures of Gaussians and the Statistics of Natural Images
The statistics of photographic images, when represented using multiscale (wavelet) bases, exhibit two striking types of non… Expand
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1998
1998
The Bias-Variance Tradeoff and the Randomized GACV
We propose a new in-sample cross validation based method (randomized GACV) for choosing smoothing or bandwidth parameters that… Expand
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Highly Cited
1997
Highly Cited
1997
Boosting the margin: A new explanation for the effectiveness of voting methods
One of the surprising recurring phenomena observed in experiments with boosting is that the test error of the generated… Expand
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Highly Cited
1987
Highly Cited
1987
Confirmation, Disconfirmation, and Informa-tion in Hypothesis Testing
Strategies for hypothesis testing in scientific investigation and everyday reasoning have interested both psychologists and… Expand
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