Python Feature Selection library from ITMO University
Project description
ITMO_FS
Feature selection library in Python
Package information:
Install with
pip install https://github.com/LastShekel/ITMO_FS/tarball/master
Current available algorithms:
Filters | Wrappers | Hybrid |
---|---|---|
Spearman correlation | Add Del | MeLiF |
Pearson correlation | Backward selection | |
Fit Criterion | Sequential Forward Selection | |
F ratio | ||
Gini index | ||
Information Gain | ||
Minimum Redundancy Maximum Relevance | ||
VDM |
To use basic filter:
from sklearn.datasets import load_iris
from filters.Filter import * # provides you a filter class, basic measures and cutting rules
data, target = load_iris(True)
res = Filter("SpearmanCorr", GLOB_CR["Best by value"](0.9999)).run(data, target)
print("SpearmanCorr:", data.shape, '--->', res.shape)
Project details
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ITMO_FS-0.1.tar.gz
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