InformativeFeatureSelection 2.0.1

Package which provides an algorithm feature selection which considers class separability and an implementation of Informative Normalized Difference Index (INDI)

Install

pip install InformativeFeatureSelection

Features

• Several implementations of feature selection algorithms based on discriminant analysis
• Binary implementation of Informative Normalized Difference Index (INDI)
• Multiclass implementation of INDI

INDI may be extremely usefully in hyperspectral imaging analysis.

Implemented algorithms were proposed in the following papers:

1. Paringer RA, Mukhin AV, Kupriyanov AV. Formation of an informative index for recognizing specified objects in hyperspectral data. Computer Optics 2021; 45(6): 873-878. DOI: 10.18287/2412-6179-CO-930.

2. Mukhin, A., Paringer, R. and Ilyasova, N., 2021, September. Feature selection algorithm with feature space separability estimation using discriminant analysis. In 2021 International Conference on Information Technology and Nanotechnology (ITNT) (pp. 1-4). IEEE.

Usage example

See jupyter notebook file in examples folder.

License

MIT License