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 :

• Scikit-learn: Machine Learning in Python, Pedregosa et al., JMLR 12, pp. 2825-2830, 2011