KNN algo

k-NN algorithm does more computation on test time rather than train time.

• True

• False

In the image below, which would be the best value for k assuming that the algorithm you are using is k-Nearest Neighbor.

• 3

• 10

• 20

• 50

Which of the following option is true about k-NN algorithm?

• It can be used for classification

• it can be used for regression

• It can be used in both classification and regression

Which of the following machine learning algorithm can be used for imputing missing values of both categorical and continuous variables?

• Linear Regression

• K-NN

• Logistic Regression

Which of the following statement is true about k-NN algorithm?

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

2-k-NN works well with a small number of features (X's), but struggles when the number of inputs is very large

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

• 1 and 2

• 1 and 3

• Only 1

• All of the above

When you find noise in data which of the following option would you consider in k-NN?

• I will increase the value of k

• I will decrease the value of k

• Noise can not be dependent on value of k

• None of these

Which of the following is true about Manhattan distance?

• It can be used for continuous variables

• It can be used for categorical variables

• It can be used for categorical as well as continuous

• None of these

Which of the following distance measure do we use in case of categorical variables in k-NN?

Hamming Distance

Euclidean Distance

Manhattan Distance

• 1

• 2

• 3

• 1 and 2

• 1, 2 and 3

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

• 1

• 2

• 4

• 8

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

• 1

• 2

• 4

• 8