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.