Feature Selection in Python with Scikit-Learn
Last Updated on June 4, 2020
Not all data attributes are created equal. More is not always better when it comes to attributes or columns in your dataset.
In this post you will discover how to select attributes in your data before creating a machine learning model using the scikit-learn library.
Kick-start your project with my new book Machine Learning Mastery With Python, including step-by-step tutorials and the Python source code files for all examples.
Let’s get started.
Update: For a more recent tutorial on feature selection in Python see the post:
Select Features
Feature selection is a process where you automatically select those features in your data that contribute most to the prediction variable or output in which you are interested.
Having too many irrelevant features in your data can decrease the accuracy of the models. Three benefits of performing feature selection before modeling your data
To finish reading, please visit source site