A simple trick for very unbalanced data (Ep. 157)

<p>Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show!</p> Sponsors <p>Get one of the best VPN at a massive discount with coupon code DATASCIENCE. It provides you with an 83% discount which unlocks the best price in the market plus 3 extra months for free. Here is the link <a href='https://surfshark.deals/DATASCIENCE'>https://surfshark.deals/DATASCIENCE</a> </p> <p> </p> References <ul><li>Leo Breiman, <a href='https://link.springer.com/content/pdf/10.1023/A:1010933404324.pdf'>Random Forests</a>, 2001</li> <li>C. Chen, A. Liaw, L. Breiman, <a href='https://statistics.berkeley.edu/tech-reports/666'>Using Random Forest to Learn Imbalanced Data</a> (2004)</li> </ul> <p> </p>