Skip to content

Feature selector is a tool for dimensionality reduction of machine learning datasets

License

Notifications You must be signed in to change notification settings

WillKoehrsen/feature-selector

Repository files navigation

Feature Selector: Simple Feature Selection in Python

Feature selector is a tool for dimensionality reduction of machine learning datasets.

Methods

There are five methods used to identify features to remove:

  1. Missing Values
  2. Single Unique Values
  3. Collinear Features
  4. Zero Importance Features
  5. 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==1.22.0
pandas==0.23.1
scikit-learn==0.19.1

Contact

Any questions can be directed to wjk68@case.edu!

About

Feature selector is a tool for dimensionality reduction of machine learning datasets

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published