A fast canonical-correlation-based feature selection method
Project description
FastCan is a python implementation of the paper
- Zhang, S., & Lang, Z. Q. (2022).
Orthogonal least squares based fast feature selection for linear classification. Pattern Recognition, 123, 108419.
- Zhang, S., Wang, T., Sun L., Worden, K., & Cross, E. J. (2024).
Canonical-correlation-based fast feature selection for structural health monitoring.
Installation
Install FastCan:
Run pip install fastcan
Examples
>>> from fastcan import FastCan >>> X = [[ 0.87, -1.34, 0.31 ], ... [-2.79, -0.02, -0.85 ], ... [-1.34, -0.48, -2.55 ], ... [ 1.92, 1.48, 0.65 ]] >>> y = [0, 1, 0, 1] >>> selector = FastCan(n_features_to_select=2, verbose=0).fit(X, y) >>> selector.get_support() array([ True, True, False])
Uninstallation
Uninstall FastCan:
Run pip uninstall fastcan
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