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A Weighted Ensemble Classification Algorithm Based on Nearest Neighbors for Multi-Label Data Stream

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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A Coupled k-Nearest Neighbor Algorithm for Multi-label Classification

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A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm

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Joint Binary Neural Network for Multi-label Learning with Applications to Emotion Classification

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Classifier Ensembles for Changing Environments

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Ensemble convolutional neural networks with weighted majority for wafer bin map pattern classification

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Ensemble pruning of ELM via migratory binary glowworm swarm optimization and margin distance minimization

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Improved discrete artificial fish swarm algorithm combined with margin distance minimization for ensemble pruning

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Cost-sensitive KNN classification

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Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams

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Adaptive ensemble of self-adjusting nearest neighbor subspaces for multi-label drifting data streams

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Joint Ranking SVM and Binary Relevance with robust Low-rank learning for multi-label classification

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ML-KNN: A lazy learning approach to multi-label learning

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A novel k NN algorithm with data-driven k parameter computation

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ML-Net: multi-label classification of biomedical texts with deep neural networks

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Analysis of Multiobjective Algorithms for the Classification of Multi-Label Video Datasets

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An adaptive k-nearest neighbor algorithm

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Multi-label Classification Using Ensembles of Pruned Sets

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Multi-Label kNN classifier with Online Dual Memory on data stream

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An Efficient Framework for Multi-Label Learning in Non-stationary Data Stream

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Multi-Label Classification Based On Subcellular Region-Guided Feature Description For Protein Localisation

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Fuzzy KNN Method With Adaptive Nearest Neighbors

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KNN Classification with One-step Computation

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Reachable Distance Function for KNN Classification

inferredcites →https://doi.org/10.1109/tnnls.2013.2251352openalex-snapshot

Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm

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Efficient kNN Classification With Different Numbers of Nearest Neighbors

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Multi-label Classification with ART Neural Networks

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A survey of active and passive concept drift handling methods

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Learning from Time-Changing Data with Adaptive Windowing

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MLCE: A Multi-Label Crotch Ensemble Method for Multi-Label Classification

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Pruning High-Similarity Clusters to Optimize Data Diversity when Building Ensemble Classifiers

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Evaluating algorithms that learn from data streams

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Learning k for kNN Classification

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GOOWE

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A Novel Online Stacked Ensemble for Multi-Label Stream Classification

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Multi-Label Punitive kNN with Self-Adjusting Memory for Drifting Data Streams

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Experimental comparisons of online and batch versions of bagging and boosting

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A streaming ensemble algorithm (SEA) for large-scale classification

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An overview of complex data stream ensemble classification

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Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift

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Distance Metric Learning for Large Margin Nearest Neighbor Classification

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MEKA: A multi-label/multi-target extension to Weka

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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A novel stacked ensemble algorithm based on feature subspace extraction and label correction for multi-label classification

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Bin.INI: An ensemble approach for dynamic data streams

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Pro-IDD: Pareto-based ensemble for imbalanced and drifting data streams

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An Adaptive Active Learning Framework for Sparsely Labeled Multi-Label Drifting Data Streams

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Unified online weak multi-Label learning in drifting and imbalanced data streams

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Homogeneous–Heterogeneous Hybrid Ensemble for concept-drift adaptation

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EMRIL: Ensemble Method based on ReInforcement Learning for binary classification in imbalanced drifting data streams

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Online multi-label classification under noisy and changing label distribution

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Multi-Label Transfer Learning in Non-Stationary Data Streams

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Weak Multi-Label Data Stream Classification Under Distribution Changes in Labels

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Imbalance-Robust Multi-Label Self-Adjusting kNN

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A Comprehensive Survey on Big Data Analytics: Characteristics, Tools and Techniques

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A Systematic Literature Review on Multi-label Data Stream Classification

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