Skip to search formSkip to main contentSkip to account menu

Classifier chains

Classifier chains is a machine learning method for problem transformation in multi-label classification. It combines the computational efficiency of… 
Wikipedia (opens in a new tab)

Related topics

Related topics

4 relations
Ensemble learningMachine learningMulti-label classificationSupport vector machine

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Speeding Up Classifier Chains in Multi-label Classification
Multi-label classification has attracted increasing attention of the scientific community in recent years, given its ability to… 
2018
2018
Dynamic Classifier Chain with Random Decision Trees
Classifiers chains (CC) is an effective approach in order to exploit label dependencies in multi-label data. However, it has the… 
2017
2017
Ordering Classifier Chains using filter model feature selection techniques
Context: Multi-label classification concerns classification with multi-dimensional output. The Classifier Chain breaks the multi… 
2015
2015
On the spectrum between binary relevance and classifier chains in multi-label classification
Two fundamental and prominent methods for multi-label classification, Binary Relevance (BR) and Classifier Chains (CC), are… 
2015
2015
Polytree-Augmented Classifier Chains for Multi-Label Classification
Multi-label classification is a challenging and appealing supervised learning problem where a subset of labels, rather than a… 
2015
2015
Classifier Circle Method for Multi-Label Learning
Exploiting label relationship to help improve learning performance is important for multi-label learning. The classifier chain… 
2013
2013
Classifier Chains for Multi-Label Classification with Incomplete Labels
Many methods have been explored in the literature of multi-label learning, ranging from simple problem transformation to more… 
2012
2012
Efficient Monte Carlo Optimization for Multi-dimensional Classifier Chains
Multi-dimensional classification (MDC) is the supervised learning problem where an instance may be associated with multiple… 
2009
2009
Simulated Iterative Classification A New Learning Procedure for Graph Labeling
Collective classification refers to the classification of interlinked and relational objects described as nodes in a graph. The… 
2006
2006
Resource Management for Chained Binary Classifiers
Networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)