scikit-hubness: high-dimensional data mining¶
scikit-hubness
is a Python package for analysis of hubness
in high-dimensional data. It provides hubness reduction and
approximate nearest neighbor search via a drop-in replacement for
sklearn.neighbors.
Getting started¶
Get started with scikit-hubness
in a breeze.
Find how to install the package and
see all core functionality applied in a single quick start example.
User Guide¶
The User Guide introduces the main concepts of scikit-hubness
.
It explains, how to analyze your data sets for hubness,
and how to use the package to lift this curse of dimensionality.
You will also find examples how to use skhubness.neighbors
for approximate nearest neighbor search (with or without hubness reduction).
API Documentation¶
The API Documentation provides detailed information
of the implemented methods.
This information includes method descriptions, parameters, references, examples, etc.
Find all the information about specific modules and functions of scikit-hubness
in this section.
History¶
A brief history of the package,
and how it relates to the Hub-Toolbox
’es.
Development¶
There are several possibilities to contribute to this free open source software. We highly appreciate all input from the community, be it bug reports or code contributions.
Source code, issue tracking, discussion, and continuous integration appear on our GitHub page.
What’s new¶
To see what’s new in the latest version of scikit-hubness
,
have a look at the changelog.