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.
- Latest release
- Jan 23, 2025
- Releases
- 9
- Known CVEs
- 0
- First release
- May 04, 2024
- License
- Apache-2.0
Repository
Source
- Stars
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- Forks
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Security score
No OpenSSF Scorecard available for this repository.
Packages from this repo
No other tracked packages from this repository.
Insights
Activity
- Total releases
- 9
- Last 12 months
- 0
- Cadence
- ~7 days
- Dependencies
- 20
Releases per month
last 12 monthsRelease mix
- minor 3
- patch 5
9
releases
Dependencies
Depends on
0.4.0-
absl-py
==1.4.0
-
cloudml-hypertune
==0.1.0.dev6
-
fastavro
==1.4.12
-
frozendict
==2.3.2
-
google-cloud-bigquery
==3.16.0
-
google-cloud-bigquery-storage
==2.24.0
-
google-cloud-storage
==2.14.0
-
joblib
==1.2.0
-
pandas
==2.2.2
-
parameterized
==0.8.1
1–10 of 20
Used by
Nothing tracked depends on this yet.
Releases
| Version | Released | |
|---|---|---|
0.4.0
minor
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0.3.3
patch
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0.3.2
patch
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0.3.1
patch
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0.3.0
minor
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0.2.2
patch
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0.2.1
patch
| ||
0.2.0
minor
| ||
0.1.0
initial
|