ldbod: Local Density-Based Outlier Detection
Flexible procedures to compute local density-based outlier scores for ranking outliers.
Both exact and approximate nearest neighbor search can be implemented, while also accommodating
multiple neighborhood sizes and four different local density-based methods. It allows for
referencing a random subsample of the input data or a user specified reference data set
to compute outlier scores against, so both unsupervised and semi-supervised outlier
detection can be implemented.
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