outlier ensembles
6 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in outlier ensembles
Most implemented papers
PyOD: A Python Toolbox for Scalable Outlier Detection
yzhao062/pyod
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PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data.
Graph-based Selective Outlier Ensembles
A problem with this approach is that poor components are likely to negatively affect the quality of the consensus result.
LSCP: Locally Selective Combination in Parallel Outlier Ensembles
The top-performing base detectors in this local region are selected and combined as the model's final output.
DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles
Selecting and combining the outlier scores of different base detectors used within outlier ensembles can be quite challenging in the absence of ground truth.
SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection
Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection.
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records Data
The ability to perform accurate prognosis of patients is crucial for proactive clinical decision making, informed resource management and personalised care.
