KNN and Decision Tree

1. KNN algorithm does more computation on test time rather than train time.

• True

• False

2. Which of the following statement is true about k-NN algorithm? (can be more than 1 answer is true)

• k-NN performs much better if all of the data have the same scale

• k-NN works well with a small number of input variables (p), but struggles when the number of inputs is very large

• k-NN makes no assumptions about the functional form of the problem being solved

Which of the following distance metric can not be used in k-NN?

• Manhattan

• Euclidean

• Chebychev

• All can be used

Which of the following will be Euclidean Distance between the two data point A(1,3) and B(2,3)?

• 1

• 2

• 4

• 8

In decision tree, the inner node represents a class

• True

• False

Which algorithm is using information gain as its splitting criteria?

• ID3

• C4.5

• CART

• All of above are true

Attribute which entropy has value 0 is purest.

• True

• False

Which of the following algorithm are not an example of ensemble learning algorithm?

• Random Forest

• Adaboost

• Gradient Boosting

• Decision Trees