hubminer: Hub Miner
Description
This is the first official release of Hub Miner, a hubness-aware machine learning library for high-dimensional data analysis.
Hub Miner offers detailed experimental frameworks for both supervised and unsupervised learning, as well as metric learning, data reduction, learning with feature or label noise. Many hubness-aware approaches are available for experimentation and there is also a decent set of standard baselines for comparisons.
This release of Hub Miner is OpenML-compatible, as it is possible to perform networked experiments via OpenML in classification experiments, fetch the data and the splits - and upload the raw results.
Many standard data formats are supported in Hub Miner and there is also basic support for handling textual and image data.
Exploratory analysis and data visualization tools are available for many aspects of data analysis, with an emphasis on evaluating the consequences of high dimensionality and hubness in particular.
Files
hubminer-v1.0.zip
Files
(3.8 MB)
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md5:9118cf41e1a2e581e16cc5d5b79c81d7
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Additional details
Related works
- Is supplement to
- https://github.com/datapoet/hubminer/tree/v1.0 (URL)