An Overview of the Most Important Features in Scikit-Learn Version 0.24

Scikit-learn, Python’s machine-learning library, just got better. It’s the best time to update it.

Recently, in December 2020, scikit-learn released a major update in version 0.24. It is the last stable release of version 0. The next release will supposedly be version 1.0 and is currently in development.

I will provide an overview of some important features introduced in version 0.24. Given a large number of highlight features, I highly recommend upgrading your scikit-learn library.

Contents:

• Upgrading to Version 0.24
• Major Features
• Other Interesting Features

Upgrading to Version 0.24

I am using Python environments, so, first I activated my desired environment, and then upgraded the scikit-learn version via pip.

## Activate the environment
>>> source activate py38

## Upgrade scikit-learn 
>>> pip install — upgrade scikit-learn
...
...
Successfully installed scikit-learn-0.24.0

Major Features

• Sequential Feature Selector (SFS)
• Individual Conditional Expectation (ICE) plots
• Successive Halving Estimators
• Semi-supervised Self Training Classifier
• Native categorical features in HistGradientBoosting
• What NOT to do with scikit-learn

#programming #python #machine-learning #data-science #scikit-learn