Towards AI Can Help your Team Adopt AI: Corporate Training, Consulting, and Talent Solutions.

Publication

Fully Understand ElasticNet Regression with Python
Artificial Intelligence   Data Science   Latest   Machine Learning

Fully Understand ElasticNet Regression with Python

Last Updated on November 5, 2023 by Editorial Team

Author(s): Amit Chauhan

Originally published on Towards AI.

Regularization method in machine learning
Photo by Boitumelo on Unsplash

In simple terms, the elastic net regression took the qualities of ridge and lasso regression to regularize the machine learning regression model.

Where do we use elastic net regression?

It helps to overcome the issues of over-fitting with ridge quality.Dealing with multi-collinearity issues in the data.Reducing features in the data with lasso quality.

Before learning elastic net, we need to revise the main algorithm concept. To do a bias-variance trade-off for reducing the over-fit issue, we can use some methods like bagging, boosting, and regularization.

Over-fitting: The model is done on training data but not well on testing data. In… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓