Overfitting? Fear Not, There’s a Way Out!

Paul OmagbemiPaul Omagbemi
1 min read

I bring thee good news. There are ways of mitigating overfitting!

  • Collect more training data. (but, but, but sometimes, collecting more data can be challenge, especially when they are not available)

  • Next thing we might want to consider is to reduce the number of features. You wanna be careful with this since reducing the features too much can result in overfitting -- except, well except if that's what you want. Also the problem with reducing the number of features is that we might not know which exactly of the feature will be crucial.

  • Lastly: Regularization.

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Written by

Paul Omagbemi
Paul Omagbemi

Exploring the language of data, one algorithm at a time. Machine learning enthusiast, AI researcher, and advocate for tech-driven solutions to real-world challenges. Passionate about using AI for public safety and ethical technology. Join me as I document my journey through data, models, and insights.