spade-anomaly-detection
Semi-supervised Pseudo Labeler Anomaly Detection with Ensembling (SPADE) is a semi-supervised anomaly detection method that uses an ensemble of one class classifiers as the pseudo-labelers and supervised classifiers to achieve state of the art results especially on datasets with distribution mismatch between labeled and unlabeled samples.
Activity
- Latest release
- 1y ago
- Total releases
- 9
- Cadence
- ~7 days
- Last 12 months
- 0
Details
- License
- Apache-2.0
- First release
- May 04, 2024
Releases