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KNN Interview Questions

                     KNN interview questions

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

A) Euclidean Distance

B) Manhatten Distance

c) Hamming Distance

E) Minkowski Distance

F) Jaccard Distance

G) All the above

Answer:- G

All of these distance metric can be used as a distance metric for KNN

2)Knn is for regression or classification?

Answer:- Knn is used for both classification and regression problems.

3) When we use Manhatten Distance?

Answer:-Manhatten distance is used for continuous variables.


4)You have given the following 2 statements, find which of these options is/are true in case of k-NN?

  1. In the case of very large value of k, we may include points from other classes into the neighborhood, so it leads to overfitting.
  2. In case of too small value of k the algorithm is very sensitive to noise.(it will affect our model performance).
Answer:-The above two points are answers.

5) which algorithm do you prefer to deal with missing values?
     a) Linear Regression
     b) Logistic Regression
     c) KNN
Answer:-KNN ( while treating missing values knn gives nearest neighbors value to fill the missing term).

6) overfitting in k-nn?
Answer:-In an overfitted module, it seems to be performing well on training data, but it is not generalized enough to give the same results on new data.

 

 

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