/ Machine Learning

A tool for dimensionality reduction of machine learning datasets

A tool for dimensionality reduction of machine learning datasets

feature-selector

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

Refer to the Feature Selector Usage notebook for how to use

The feature selector is a tool for removing features for a dataset intended
for machine learning. 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

The FeatureSelector also includes a number of visualization methods to inspect
characteristics of a dataset.

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

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