Question: 1

Which of the following metrics are used to evaluate classification models?

Question: 2

Which one is a classification algorithm?

Question: 3

Classification is-

Question: 4

You have a dataset of different flowers containing their petal lengths and color. Your model has to predict the type of flower for given petal lengths and color. This is a-

Question: 5

A classifier-

Question: 6

Classification is appropriate when you-

Question: 7

With the help of a confusion matrix, we can compute-

Question: 8

What does recall refer to in classification?

Question: 9

False negatives are-

Question: 10

Suppose your classification model predicted true for a class which actual value was false. Then this is a-

Question: 11

The false negative value is 5 and the true positive value is 20. What will be the value of recall-

Question: 12

The true positive value is 10 and the false positive value is 15. Calculate the value of precision-

Question: 13

If the precision is 0.6 and the recall value is 0.4. What will be the f measure?

Question: 14

Which one is a different algorithm?

Question: 15

What is a support vector?

Question: 16

Which of the following is a lazy learning algorithm?

Question: 17

Which of the following is not a lazy learning algorithm?

Question: 18

What is the most widely used distance metric in KNN?

Question: 19

Which of the following is the best algorithm for text classification?

Question: 20

What does k stand for in the KNN algorithm?

Question: 21

Support Vector Machine is-

Question: 22

What are hyperplanes?

Question: 23

What is a kernel?

Question: 24

Which of the following is not a kernel?

Question: 25

Why Naive Bayes is called naive?

Question: 26

For two events A and B, the Bayes theorem will be-

Question: 27

How does a decision tree work?

Question: 28

Suppose you have a dataset that is randomly distributed. What will be the best algorithm for that dataset?

Question: 29

Which pair of the algorithms are similar in operation?

Question: 30

Which metric is not used for evaluating classification models?