Machine Learning

Question 1

Which method always gives the same global optimum?

Answer 1

Logistic regression

Question 2

Which method is not iterative?

Answer 2

Naïve Bayes

Question 3

Which of the following is a feature selection technique?

Answer 3

Stepwise regression

Question 4

Which method uses a gradient descent algorithm to find the optimum?

Answer 4

Logistic regression

Question 5

Which method is most prone to overfitting?

Answer 5

Neural network

Question 6

Which method is used in deep learning?

Answer 6

Neural network

Question 7

Which model uses the following formula :

P() = P() * P() / sum[P() p()]?

Answer 7

Naive Bayes or SVM

Question 8

You have a dataset with 10,000 data and 20,000 features. Which method that splits the data into hyperplanes is most suited to classify new data?

Answer 8

SVM

Question 9

Why, in essence, do we try to find a posteriori probabilities?

Answer 9

To minimize the error rate

Question 10

Which of the following is not an issue for decision trees?

Answer 10

Computationally intensive