pyCFOF
Pour commencer
Installation
Lancer pip install -r requirements.txt ou python3 -m pip install -r requirements.txt.
Ou à partir du dépôt pip install Concentration-Free-Outlier-Factor.
Utilisation
>>> from pyCFOF import ConcentrationFreeOutlierFactor as CFOF
>>> X = [[-1.1], [0.2], [101.1], [0.3]]
>>> cfof = CFOF(n_neighbors=len(X), rho=[0.1])
>>> cfof.fit_predict(X)
array([[ 1],
[ 1],
[-1],
[ 1]])
>>> cfof.outlier_factor_
array([[0.75],
[0.5 ],
[1. ],
[0.5 ]])
Remerciements
Développements des travaux de :
- Fabrizio Angiulli, CFOF: A Concentration Free Measure for Anomaly Detection. ACM Transactions on Knowledge Discovery from Data (TKDD), 14(1):Article 4, 2020
Utilisation de :
1 maintainer
Metadata
1 maintainer
Release files for Concentration-Free-Outlier-Factor 0.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Concentration Free Outlier Factor-0.3.1.tar.gz | 6.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Concentration_Free_Outlier_Factor-0.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 14.9 kB
Release files / Concentration Free Outlier Factor-0.3.1.tar.gz
| Download URL | Concentration Free Outlier Factor-0.3.1.tar.gz |
|---|---|
| Size | 6.9 kB |
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Release files / Concentration_Free_Outlier_Factor-0.3.1-py3-none-any.whl
| Download URL | Concentration_Free_Outlier_Factor-0.3.1-py3-none-any.whl |
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| Size | 8.0 kB |
| Tags | Python 3 |
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