Fractal Analytics Data Analytics Intern Interview Questions and Answers

Bagging and Boosting are ensemble learning techniques used to improve model performance.

• Bagging involves training multiple models on different subsets of the data and averaging their predictions.

• Boosting involves training models sequentially, with each model focusing on the errors of the previous model.

• Bagging reduces variance and overfitting, while boosting reduces bias and underfitting.

• Examples of bagging algorithms ...read more

Logistic regression is used when the dependent variable is categorical, while linear regression is used for continuous variables.

• Logistic regression predicts the probability of an event occurring, while linear regression predicts the value of a dependent variable.

• Logistic regression uses a sigmoid function to map the output to a probability value between 0 and 1.

• Linear regression assumes a linear relationship between t...read more