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#local_outlier_factor

Local outlier factor

Algorithm for anomaly detection

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 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.

Tue 21st

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Local outlier factor Outlier Anomaly detection Unsupervised learning Q-learning GPT-1 Multilayer perceptron Vector database Mixture of experts Outline of machine learning
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