FAQ

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… (More)
Wikipedia

Topic mentions per year

Topic mentions per year

2005-2016
0120052016

Related topics

Related topics

23 relations
AlgorithmArtificial neural networkBoostingBootstrap aggregating
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Broader (1)

Machine learning

Related mentions per year

Related mentions per year

1936-2019
19401960198020002020
Bias–variance tradeoff
Algorithm
Statistical classification
Artificial neural network
Machine learning
Feature selection

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Bias-variance decomposition of errors in data-driven land cover change modeling
Careful model evaluation is essential for using the results of data-driven land cover change (LCC) models. A useful evaluation… (More)
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2013
2013
Bias-variance decomposition of ir evaluation
It has been recognized that, when an information retrieval (IR) system achieves improvement in mean retrieval effectiveness (e.g… (More)
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2011
2011
Bias Plus Variance Decomposition for Survival Analysis Problems
Bias variance decomposition of the expected error defined for regression and classification problems is an important tool to… (More)
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2009
2009
Bias-Variance Decomposition for model selection
Bias-variance decomposition is known to be a powerful tool when explaining the success of learning methods. By now it’s common… (More)
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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… (More)
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2006
2006
Improved Behavior Knowledge Space Combination Method with Observational Learning
A new combination model, which incorporated observational learning with Behavior Knowledge Space (BKS) method, was proposed in… (More)
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2005
2005
A Temporal Minimum Description Length Policy for Evolving Neural Networks
One of the most important issues for computational methods is their time complexity. This paper introduces a temporal MDL… (More)
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