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Bootstrap aggregating

Known as: Bootstrap aggregation, Bootstrapped Aggregation, Bootstrapping (machine learning) 
Bootstrap aggregating, also called bagging, is a machine learning ensemble meta-algorithm designed to improve the stability and accuracy of machine… 
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Related topics

Related topics

22 relations
AdaBoostBias–variance tradeoffBoosting (machine learning)Bootstrapping (statistics)

Broader (1)

Computational statistics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
On the Performance of Ensemble Learning for Automated Diagnosis of Breast Cancer
The automated diagnosis of diseases with high accuracy rate is one of the most crucial problems in medical informatics. Machine… 
Review
2012
Review
2012
A Study Of Bagging And Boosting Approaches To Develop Meta-Classifier
-- Classification is one of the data mining techniques that analyses a given data set and induces a model for each class based on… 
2011
2011
Shortipedia aggregating and curating Semantic Web data
Highly Cited
2009
Highly Cited
2009
Reducing Semantic Drift with Bagging and Distributional Similarity
Iterative bootstrapping algorithms are typically compared using a single set of hand-picked seeds. However, we demonstrate that… 
2009
2009
Regression-Based Summarization of Email Conversations
In this paper we present a regression-based machine learning approach to email thread summarization. The regression model is… 
2008
2008
Constraint Projections for Ensemble Learning
It is well-known that diversity among base classifiers is crucial for constructing a strong ensemble. Most existing ensemble… 
Highly Cited
2003
Highly Cited
2003
Distributed learning with bagging-like performance
2003
2003
Texture classification of logged forests in tropical Africa using machine-learning algorithms
This Letter describes a procedure that incorporates textural measures in the classification of logged forests from Landsat… 
2003
2003
Ensemble Techniques for Parallel Genetic Programming Based Classifiers
An extension of Cellular Genetic Programming for data classification to induce an ensemble of predictors is presented. Each… 
2000
2000
Bagging and Boosting a Treebank Parser
Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these… 
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