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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
Hybrid and Blind Steganographic Method for Digital Images Based on DWT and Chaotic Map
Steganography is the art and science of hiding secret information into digital media with the intention to transmit this… 
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… 
2012
2012
Similarity-based spectral clustering ensemble selection
Traditional clustering ensemble methods combine all the obtained clustering results at hand. However, we can often achieve a… 
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… 
2009
2009
Face Classification Using Gabor Wavelets and Random Forest
This paper presents a new face classification techniquebased on Gabor wavelets and Random Forest. Random Forest is a tree based… 
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… 
2006
2006
Hierarchical ensemble of Gabor Fisher classifier for face recognition
Gabor feature has been widely recognized as one of the best representations for face recognition. However, traditionally, it has… 
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… 
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… 
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