Boosting algorithm improves the accuracy of juvenile forensic dental age estimation in southern china population

HIGHLIGHTS

• who: Weijie Shan from the SchoolMedical University have published the Article: Boosting algorithm improves the accuracy of juvenile forensic dental age estimation in southern China population, in the Journal: Scientific Reports Scientific Reports
• what: This research study was conducted retrospectively from data obtained for clinical purposes. The effectiveness of each machine_learning algorithm in optimizing the model was compared, and the results showed that LightGBM, XGBoost, extra -trees, decision tree, CatBoost and GBDT were effective in improving the estimation of the model, with XGBoost, CatBoost and GBDT all being algorithms under the boosting framework. 0.495 . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or E-mail:

  If you don't have an account, you can create one here.