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.
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… 
2016
2016
Using tensor products to detect unconditional label dependence in multilabel classifications
2015
2015
Semi-supervised Multi-label k-Nearest Neighbors Classification Algorithms
Classification is one of the most traditional tasks in machine learning. In supervised learning for classification, the goal is… 
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
Context-aware MIML instance annotation: exploiting label correlations with classifier chains
In multi-instance multi-label (MIML) instance annotation, the goal is to learn an instance classifier while training on a MIML… 
2013
2013
Multi-Label Classification Using Dependent and Independent Dual Space Reduction
While multi-label classification can be widely applied for problems where multiple classes can be assigned to an object, its… 
2009
2009
Classification tree Sources
The separation of source coding into two stages, modeling and encoding, is a highly successful approach. We propose meta-modeling… 
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)