KNN Algorithm

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

k-NN algorithm can be used in both classification and regression

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

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

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

• Manhattan

• Minkowski

• Euclidean

• All can be used

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

• K-NN

• Linear Regression

• Logistic Regression

• ANN

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

• Minkowski Distance

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

• 1

• 2

• 3

• 4

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

• 1

• 2

• 3

• 4