‘MIset’ stands for ‘(M)utual (I)nformation (SET) of feature selection techniques’.
This is a library that provides a python implementation of the mutual information based feature selection techniques outlined in the following research papers:
‘Joint Mutual Information Maximization’ method as described here: https://doi.org/10.1016/j.eswa.2015.07.007.
‘Normalized Joint Mutual Information Maximization’ method as described here: https://doi.org/10.1016/j.eswa.2015.07.007.
‘Joint Mutual Information with Class Relevance’ method as described here: https://doi.org/10.1016/j.jcmds.2023.100075.
Installation
To install use:
$ pip install misetNote
It is generally recommended to apply binning to both continuous and discrete variables before using this feature selection technique, as this was the approach taken by its authors. If binning is ignored on discrete or continuous variables, the MIset package will treat each distinct value of these variables as its own seperate category by default.
Requirements
pandas
numpy
joblib
Read the documentation at: https://miset.readthedocs.io/en/latest/index.html
1 maintainer
Release files for MIset 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| miset-1.1.0.tar.gz | 7.7 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| miset-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.7 MB
Release files / miset-1.1.0.tar.gz
| Download URL | miset-1.1.0.tar.gz |
|---|---|
| Size | 7.7 MB |
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Release files / miset-1.1.0-py3-none-any.whl
| Download URL | miset-1.1.0-py3-none-any.whl |
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| Size | 8.0 kB |
| Tags | Python 3 |
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