Performance Based Feature selection Technique: Prototype
Project description
This is a PBFS (Performance-Based Feature Selection) Library.
The library has functions which predict the effect of features on ML models based on pre-trained ML models. Library owners: Movin Fernandes, Hong Zhu.
This was created as a part of Dissertation project for MSc Data Analytics alongside Research.
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CHANGE LOG For Performance based Feature Selection Technique
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Latest Changes
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|| 2.0.0 -- Latest update - Consists of updates to descriptions, python code, metadata.
|| 1.0.8 -- bug fixes
|| 1.0.7 -- path fixes v4
|| 1.0.6 -- path fixes v3
|| 1.0.5 -- path fixes v2
|| 1.0.4 -- path fixes
|| 1.0.3 -- path fixes for users to use the function call
|| 1.0.2 -- bug fixes for users to use the function call
|| 1.0.0.2 -- Bug fixes, path fixes.
|| 1.0.0.1 -- Bug fixes, path fixes.
|| 1.0.0 -- First Release to PYPI
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