Feature Selection in Machine Learning

In this short video, Max Margenot gives an overview of selecting features for your model. He goes over the process of adding parameters to your model while avoiding overfitting. He also discusses general tools for evaluating the quality of different features, many contained in packages like scikit-learn, and covers methods of testing the various features in your algorithm. Explore feature selection on Quantopian: https://www.quantopian.com/lectures/m.... Special thanks to Cheng Peng from the Quantopian Community for suggesting this video. Feel free to leave suggestions for any content that you would like to see at https://www.quantopian.com/posts/what.... Subscribe to our Channel to be notified when we make a new video. As always, if there are any topics you would like us to focus on for future videos, please send us a quick note at [email protected]. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.