Bridgei2i Analytics Solutions Interview Questions, Process, and Tips

Random Forest and XGBoost are both ensemble learning algorithms used for classification and regression tasks.

• Random Forest is a bagging algorithm that builds multiple decision trees and combines their outputs to make a final prediction.

• XGBoost is a boosting algorithm that builds decision trees sequentially, with each tree correcting the errors of the previous one.

• Random Forest is less prone to overfitting and can handl...read more

Random Forest is an ensemble of Decision Trees that improves accuracy and reduces overfitting.

• Decision Trees are simple and easy to interpret, but prone to overfitting.

• Random Forest combines multiple Decision Trees to reduce overfitting and improve accuracy.

• Random Forest can handle missing values and outliers better than Decision Trees.

• Decision Trees are faster to train and predict than Random Forest.

• Random Forest is s...read more

Append and Merge are two methods used to combine data from multiple sources into a single dataset.

• Append adds new rows to an existing dataset.

• Merge combines two or more datasets based on a common column or key.

• Append is useful when adding new data to an existing dataset, while Merge is useful for combining datasets with related information.

• Example: Appending new sales data to an existing sales dataset.

• Example: Merging ...read more