FastEMC is a method for dimensionality reduction.
Fast Exponential Monte Carlo
FastEMC is a modified version of exponential Monte Carlo. FastEMC takes class features and labels as input, and returns a list of scores and a list of selected features. The score is based on logistic regression. Two logistic regression classifiers are used:
- a fast classifier with limited training,
- and a slow classifier with full training.
The fast classifier is used to explore feature space rapidly. Features are occasionaly compared using the slow classifier.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size fastemc-0.0.1-py3-none-any.whl (16.3 kB)||File type Wheel||Python version py3||Upload date||Hashes View hashes|
|Filename, size fastemc-0.0.1.tar.gz (3.1 kB)||File type Source||Python version None||Upload date||Hashes View hashes|