ML-overall

Which of the following is a widely used and effective machine learning algorithm based on the idea of bagging?

• Decision Tree

• Regression

• Classification

• Random Forest

To find the minimum or the maximum of a function, we set the gradient to zero because:

• The value of the gradient at extrema of a function is always zero

• Depends on the type of problem

• Both A and B

• None of the above

The most widely used metrics and tools to assess a classification model are:

• Confusion matrix

• Cost-sensitive accuracy

• Area under the ROC curve

• All of the above

Which of the following is a good test dataset characteristic?

• Large enough to yield meaningful results

• Is representative of the dataset as a whole

• Both A and B

• None of the above

Which of the following is a disadvantage of decision trees?

• Factor analysis

• Decision trees are robust to outliers

• Decision trees are prone to be overfit

• None of the above

How do you handle missing or corrupted data in a dataset?

• Drop missing rows or columns

• Replace missing values with mean/median/mode

• Assign a unique category to missing values

• All of the above

What is the purpose of performing cross-validation?

• To assess the predictive performance of the models

• To judge how the trained model performs outside the sample on test data

• Both A and B

Why is second order differencing in time series needed?

• To remove stationarity

• find the maxima or minima at the local point

• Both A and B

• None of the above

When performing regression or classification, which of the following is the correct way to preprocess the data?

• Normalize the data → PCA → training

• PCA → normalize PCA output → training

• Normalize the data → PCA → normalize PCA output → training

• None of the above

Which of the folllowing is an example of feature extraction?

• Constructing bag of words vector from an email

• Applying PCA projects to a large high-dimensional data

• Removing stopwords in a sentence

• All of the above