The Local Outlier Factor (LOF) algorithm is an unsupervised anomaly detection method which computes the local density deviation of a given data point with respect to its neighbors. It considers as outliers the samples that have a substantially lower density than their neighbors.

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.

The local outlier factor (LOF) of a sample captures its supposed ‘degree of abnormality’. It is the average of the ratio of the local reachability density of a sample and those of its k-nearest neighbors.

Aug 31, 2020 · Local outlier factor (LOF) is an algorithm that identifies the outliers present in the dataset. But what does the local outlier mean? When a point is considered as an outlier based on its local neighborhood, it is a local outlier. LOF will identify an …

Jul 6, 2020 · The Local Outlier Factor (LOF) algorithm is an unsupervised anomaly detection method which computes the local density deviation of a given data point with respect to its neighbors. It...

Jan 9, 2023 · The Local Outlier Factor (LOF) is an algorithm for identifying anomalous data points in a dataset. It does this by measuring the local density of points around each data point and comparing it to the densities of points around other data points.

May 18, 2024 · LOF, a density-based anomaly detection method, has garnered attention for its ability to detect outliers in both structured and unstructured data. In this comprehensive guide, …

This example compares two outlier detection algorithms, namely Local Outlier Factor (LOF) and Isolation Forest (IForest), on real-world datasets available in sklearn.datasets. The goal is to show tha...

May 6, 2022 · Local outlier factor (LOF) is an algorithm used for Unsupervised outlier detection. It produces an anomaly score that represents data points which are outliers in the data set. It does this by measuring the local density deviation of a given …

Jun 8, 2024 · A well-known technique for local outlier detection is the Local Outlier Factor (LOF). LOF is an unsupervised ML algorithm. It identifies outliers relative to their local neighbourhood....