Tiger Corporation Senior Data Science Analyst Interview Questions and Answers

Coding and MCQ from hacker earth

Q1. What is random forest and how bagging and boosting differs?
Ans. 
Random forest is an ensemble learning method that builds multiple decision trees and combines their predictions.
• Random forest is a type of ensemble learning method used for classification and regression tasks.

• It builds multiple decision trees during training and combines their predictions to improve accuracy and reduce overfitting.

• Bagging (Bootstrap Aggregating) is a technique used in random forests where each tree is ...read more
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Q2. What are classification metrics?
Ans. 
Classification metrics are used to evaluate the performance of a classification model by measuring its accuracy, precision, recall, F1 score, and more.
• Classification metrics help in assessing how well a model is performing in terms of predicting the correct class labels.

• Common classification metrics include accuracy, precision, recall, F1 score, ROC-AUC, and confusion matrix.

• Accuracy measures the overall correctness of...read more
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Q1. This is managerial+ technical round You will be asked project level questions and problem solving
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