Ensembling machine learning models - Article proposal

[saheedniyi02]

Ensembling machine learning models.

Topic: Ensembling machine learning models A tutorial on how you can improve your machine learning model's performance using ensembling techniques like stacking, boosting, bagging and so on.

Outline:

• Prerequisite for the tutorial
• Dataset used (information about the kaggle dataset)
• Libraries used
• Cleaning the data (filling missing values and converting categorical to numerical values)
• Model training *Boosting (1st method of ensembling, explanation and code to apply boosting algorithms on the dataset)
  • Voting (explanation and code to apply voting ensembling approach on the dataset).
  • Stacking (explanation and code to apply Stacking ensembling approach on the dataset).
  • Bagging (explanation and code to apply Bagging ensembling approach on the dataset).
  • Effects of ensembling on the model's performance?
  • What is the best ensembling method?
  • Is ensembling worth it?
  • Conclusion

My content is

• [ ] A Tutorial