Academic Writing on Random Forest and XGBoost.
Budget ₹600-1500 INR
Explain the following topics in 7 to 12 pages.
*The topic is on CLASSIFICATION decision trees*
- Explain how a decision tree works (in detail): include how are the splits done, what metrics are taken in consideration. How is impurity determined?
- Main characteristic of a decision tree and define the most important hyperparameters
- Explain bagging vs boosting technique
- Explain the concept of the random forest algorithm
- Explain the concept of the extreme gradient boosting (XGBoost) algorithm
- Discuss why random forests and XGBoost models easily overfit to the data.
- Explain the importance of hyperparameter tuning and mention the most important hyperparameters
Important remarks:
- There should be references using the APA format and cite accordingly.
- You should use mathematical formulations when applicable
- Any time of pictures/images is welcome as long as it is cited and referenced accordingly.
- Provide examples when applicable
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This work will be done easily i have 4+ year of experience in this particular field. All of the facts and figures will be added to make this project presentable.
8 freelancere byder i gennemsnit ₹1431 timen for dette job
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