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Ensemble learning

Known as: Ensemble Algorithms, Ensemble Methods, Ensemble 
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained… 
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Related topics

Related topics

34 relations
Anomaly detectionBackpropagationBayesian structural time seriesBias–variance tradeoff

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
2014
Review
2014
A Survey of Stream Classification Algorithms
  • C. Aggarwal
  • Data Classification: Algorithms and Applications
  • 2014
  • Corpus ID: 18986073
9. 
2013
2013
DUET: integration of dynamic and static analyses for malware clustering with cluster ensembles
Automatic malware clustering plays a vital role in combating the rapidly growing number of malware variants. Most existing… 
2011
2011
Hierarchical Hybrid Decision Tree Fusion of Multiple Hyperspectral Data Processing Chains
In many practical applications of hyperspectral remotely sensed data, maps of different land cover classes or features of… 
Highly Cited
2010
Highly Cited
2010
A Fault Diagnosis Method for Industrial Gas Turbines Using Bayesian Data Analysis
This paper presents an offline fault diagnosis method for industrial gas turbines in a steady-state. Fault diagnosis plays an… 
2009
2009
A Multi-partition Multi-chunk Ensemble Technique to Classify Concept-Drifting Data Streams
We propose a multi-partition, multi-chunk ensemble classifier based data mining technique to classify concept-drifting data… 
2007
2007
Spoken Language Recognition Using Ensemble Classifiers
In this paper, we study a novel approach to spoken language recognition using an ensemble of binary classifiers. In this… 
Highly Cited
2007
Highly Cited
2007
On-Line Ensemble SVM for Robust Object Tracking
In this paper, we present a novel visual object tracking algorithm based on ensemble of linear SVM classifiers. There are two… 
Review
2004
Review
2004
Returns to Schooling and Bayesian Model Averaging: A Union of Two Literatures
In this paper, we review and unite the literatures on returns to schooling and Bayesian model averaging. We observe that most… 
2002
2002
Option pricing under model and parameter uncertainty using predictive densities
The theoretical price of a financial option is given by the expectation of its discounted expiry time payoff. The computation of… 
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