First Hub Miner release

October 18th, 2014

This is the announcement for the first release of Hub Miner code.

Hub Miner is the machine learning library that I have been working on during the course of my Ph.D. research. It is written in Java and released as open source on GitHub. This is the first release and updates are already underway, so please be a little patient. The code is well documented, with many comments – but the library is quite large and it is not that easy to navigate without a manual.

Luckily, a full manual should be done by the end of October and will also appear on GitHub along with the code, as well as on this website, under the Hub Miner page.

Hub Miner is a hubness-aware machine learning library and it implements methods for classification, clustering, instance selection, metric learning, stochastic optimization – and more. It handles standard data types and can handle both dense and sparse data types, continuous and discrete and discretized features. There is some basic implemented support for text and image data processing.

Image Hub Explorer is also within Hub Miner source, a GUI for visual hubness inspection in image data.

A powerful experimentation framework under learning.supervised.evaluation.cv.BatchClassifierTester and learning.unsupervised.evaluation.BatchClusteringTester allows for testing the various baselines in challenging conditions.

OpenML support is also under way and should be completed by the end of October, so expect it to appear in the next release.

Comments are closed.