API Documentation

This is the API documentation for scikit-hubness.

Analysis: skhubness.analysis

The skhubness.analysis package provides methods for measuring hubness.

analysis.Hubness

Hubness characteristics of data set.

Neighbors: skhubness.neighbors

The skhubness.neighbors package is a drop-in replacement for sklearn.neighbors, providing all of its features, while adding transparent support for hubness reduction and approximate nearest neighbor search.

neighbors.BallTree	BallTree for fast generalized N-point problems
neighbors.DistanceMetric	DistanceMetric class
neighbors.KDTree	KDTree for fast generalized N-point problems
neighbors.HNSW
neighbors.KNeighborsClassifier	Classifier implementing the k-nearest neighbors vote.
neighbors.KNeighborsRegressor	Regression based on k-nearest neighbors.
neighbors.LSH
neighbors.NearestCentroid	Nearest centroid classifier.
neighbors.NearestNeighbors	Unsupervised learner for implementing neighbor searches.
neighbors.RadiusNeighborsClassifier	Classifier implementing a vote among neighbors within a given radius
neighbors.RadiusNeighborsRegressor	Regression based on neighbors within a fixed radius.
neighbors.kneighbors_graph	Computes the (weighted) graph of k-Neighbors for points in X
neighbors.radius_neighbors_graph	Computes the (weighted) graph of Neighbors for points in X
neighbors.KernelDensity	Kernel Density Estimation
neighbors.LocalOutlierFactor	Unsupervised Outlier Detection using Local Outlier Factor (LOF)
neighbors.NeighborhoodComponentsAnalysis	Neighborhood Components Analysis

Reduction: skhubness.reduction

The skhubness.reduction package provides methods for hubness reduction.

reduction.MutualProximity	Hubness reduction with Mutual Proximity.
reduction.LocalScaling	Hubness reduction with local scaling.