Nutanix E Learning Developer Interview Questions and Answers

Train a Decision Tree based on provided dataset.

• Preprocess the dataset by handling missing values and encoding categorical variables.

• Split the dataset into training and testing sets.

• Train the Decision Tree model on the training set.

• Evaluate the model's performance on the testing set using metrics like accuracy or F1 score.

Feature selection can be done using techniques like filter methods, wrapper methods, and embedded methods.

• Filter methods involve selecting features based on statistical measures like correlation, chi-squared test, etc.

• Wrapper methods use a specific machine learning algorithm to evaluate the importance of features through iterative selection.

• Embedded methods incorporate feature selection within the model training proces...read more