FeatureSelector is a class for removing features for a dataset intended for machine learning
Project description
Feature Selector: Simple Feature Selection in Python
Feature selector is a tool for dimensionality reduction of machine learning datasets.
Install
pip install feature_selector
Methods
There are five methods used to identify features to remove:
- Missing Values
- Single Unique Values
- Collinear Features
- Zero Importance Features
- Low Importance Features
Usage
Refer to the Feature Selector Usage notebook for how to use
Visualizations
The FeatureSelector
also includes a number of visualization methods to inspect
characteristics of a dataset.
Correlation Heatmap
Most Important Features
Requires:
python==3.6+
lightgbm==2.1.1
matplotlib==2.1.2
seaborn==0.8.1
numpy==1.14.5
pandas==0.23.1
scikit-learn==0.19.1
Contact
Any questions can be directed to wjk68@case.edu!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
feature_selector-1.0.0.tar.gz
(9.6 kB
view hashes)
Built Distribution
Close
Hashes for feature_selector-1.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | ad5c439512d84352a4422cd30a40314501b83c08324e4d9f1848490793815fa3 |
|
MD5 | 069478ebbce78d92f5dccff934b2a2c7 |
|
BLAKE2b-256 | 7cd25448f8af6d3507f3c455429744c6436fdf3b91d10c75f4857d8e8bb4da1c |