Added api.anomaly.LocalOutlierFactor, which is an online version of the LOF algorithm for anomaly detection that matches the scikit-learn implementation.
Implementation of the api.anomaly.StandardAbsoluteDeviation algorithm, which is a uni-variate anomaly detection algorithm, based on the implementation in PySAD (Python Streaming Anomaly Detection)
Addition of the - sign before the fading_factor in accordance with the algorithm 2 proposed by Hashler and Bolanos (2016) to allow clusters with low weights to be removed.
The new micro_cluster is added with the key derived from the maximum key of the existing micro clusters. If the set of micro clusters is still empty (len = 0), a new micro cluster is added with key 0.
cluster_is_up_to_date is set to True at the end of the self._recluster() function.
Shared density graph update timestamps are initialized with the current timestamp value
neighbour_neighbours are appended correctly to the seed_set when generating cluster labels
When building weighted adjacency matrix the algorithm accounts for possibly orphaned entries in shared density graph
Added datasets.WebTraffic, which is a dataset that counts the occurrences of events on a website. It is a multi-output regression dataset with two outputs.
Add drift.NoDrift to allow disabling the drift detection capabilities of models. This detector does nothing and always returns False when queried whether or not a concept drift was detected.
Simplify inner the structures of forest.ARFClassifier and forest.ARFRegressor by removing redundant class hierarchy. Simplify how concept drift logging can be accessed in individual trees and in the forest as a whole.
Fix a bug in tree.splitter.NominalSplitterClassif that generated a mismatch between the number of existing tree branches and the number of tracked branches.
Fix a bug in tree.ExtremelyFastDecisionTreeClassifier where the split re-evaluation failed when the current branch's feature was not available as a split option. The fix also enables the tree to pre-prune a leaf via the tie-breaking mechanism.
Implementation of the incremental Kolmogorov-Smirnov statistics (at stats.KolmogorovSmirnov), with the option to calculate either the original KS or Kuiper's test.