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- 1. Multiple Choice
k-NN algorithm does more computation on test time rather than train time.
True
False
- 2. Multiple Choice
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
- 3. Multiple Choice
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
- 4. Multiple Choice
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
- 5. Multiple Choice
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
- 6. Multiple Choice
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
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