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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.
2018
2018
Joint Learning of POS and Dependencies for Multilingual Universal Dependency Parsing
This paper describes the system of team LeisureX in the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal… 
2013
2013
Artificial neural network based on rotation forest for biomedical pattern classification
The novel classifier system based on ensemble classifier is proposed in this paper. Rotation forest algorithm based on principal… 
2012
2012
Robust Object Tracking Based on Tracking-Learning-Detection
Current state-of-the-art methods for object tracking perform adaptive tracking-by-detection, meaning that a detector predicts the… 
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… 
2008
2008
Exploiting Unlabeled Text with Different Unsupervised Segmentation Criteria for Chinese Word Segmentation
This paper presents a novel approach to improve Chinese word seg- mentation (CWS) that attempts to utilize unlabeled data such as… 
2005
2005
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-the-art performance for the text classification (TC) tasks. Due to… 
2003
2003
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their… 
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… 
2002
2002
Accounting for conceptual model uncertainty via maximum likelihood Bayesian model averaging
Analyses of groundwater flow and transport typically rely on a single conceptual model of site hydrogeology. Yet hydrogeological… 
Review
1998
Review
1998
Bayesian Information Criterion for Censored Survival Models 1
We investigate the Bayesian Information Criterion (BIC) for variable selection in models for censored survival data. Kass and… 
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