In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in...

In statistics, an outlier is a data point that differs significantly from other observations. An outlier may be due to a variability in the measurement...

In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification...

{\displaystyle \gamma ^{\Delta t}} , where γ {\displaystyle \gamma } (the discount factor) is a number between 0 and 1 ( 0 ≤ γ ≤ 1 {\displaystyle 0\leq \gamma \leq...

DBSCAN, and OPTICS algorithm Anomaly detection methods include: Local Outlier Factor, and Isolation Forest Approaches for learning latent variable models...

{\displaystyle i} . The derivative to be calculated depends on the induced local field v j {\displaystyle v_{j}} , which itself varies. It is easy to prove...

Conditional random field Hidden Markov Anomaly detection RANSAC k-NN Local outlier factor Isolation forest Artificial neural network Autoencoder Deep learning...

Conditional random field Hidden Markov Anomaly detection RANSAC k-NN Local outlier factor Isolation forest Artificial neural network Autoencoder Deep learning...

Conditional random field Hidden Markov Anomaly detection RANSAC k-NN Local outlier factor Isolation forest Artificial neural network Autoencoder Deep learning...

Kernel principal component analysis Leabra Linde–Buzo–Gray algorithm Local outlier factor Logic learning machine LogitBoost Manifold alignment Markov chain...