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Dear candidates you will find MCQ questions of Machine Learning (ML) here. Learn these questions and prepare yourself for coming examinations and interviews. You can check the right answer of any question by clicking on any option or by clicking view answer button.

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Mr. Dubey • 51.17K Points
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Q. 211) Decision Tree is

(A) flow-chart
(B) structure in which internal node represents test on an attribute, each branch represents outcome of test and each leaf node represents class label
(C) both a & b
(D) class of instance
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Mr. Dubey • 51.17K Points
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Q. 212) Which of the following is true about Manhattan distance?

(A) it can be used for continuous variables
(B) it can be used for categorical variables
(C) it can be used for categorical as well as continuous
(D) it can be used for constants
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Mr. Dubey • 51.17K Points
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Q. 213) A company has build a kNN classifier that gets 100% accuracy on training data. When they deployed this model on client side it has been found that the model is not at all accurate. Which of the following thing might gone wrong? Note: Model has successfully deployed and no technical issues are found at client side except the model performance

(A) it is probably a overfitted model
(B) ??it is probably a underfitted model
(C) ??can’t say
(D) wrong client data
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Mr. Dubey • 51.17K Points
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Q. 214) hich of the following classifications would best suit the student performance classification systems?

(A) if...then... analysis
(B) market-basket analysis
(C) regression analysis
(D) cluster analysis
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Mr. Dubey • 51.17K Points
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Q. 215) Which statement is true about the K-Means algorithm? Select one:

(A) the output attribute must be cateogrical.
(B) all attribute values must be categorical.
(C) all attributes must be numeric
(D) attribute values may be either categorical or numeric
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Mr. Dubey • 51.17K Points
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Q. 216) Which of the following can act as possible termination conditions in K-Means?
1. For a fixed number of iterations.
2. Assignment of observations to clusters does not change between iterations. Except for cases with a bad local minimum.
3. Centroids do not change between successive iterations.
4. Terminate when RSS falls below a threshold.

(A) 1, 3 and 4
(B) 1, 2 and 3
(C) 1, 2 and 4
(D) 1,2,3,4
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Mr. Dubey • 51.17K Points
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Q. 217) 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 input variables (p), 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

(A) 1 and 2
(B) 1 and 3
(C) only 1
(D) 1,2 and 3
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Mr. Dubey • 51.17K Points
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Q. 218) In which of the following cases will K-means clustering fail to give good results? 1) Data points with outliers 2) Data points with different densities 3) Data points with nonconvex shapes

(A) 1 and 2
(B) 2 and 3
(C) 1, 2, and 3??
(D) 1 and 3
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Mr. Dubey • 51.17K Points
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Q. 219) How will you counter over-fitting in decision tree?

(A) by pruning the longer rules
(B) by creating new rules
(C) both by pruning the longer rules’ and ‘ by creating new rules’
(D) over-fitting is not possible
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Mr. Dubey • 51.17K Points
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Q. 220) Skewness of Normal distribution is ___________

(A) negative
(B) positive
(C) 0
(D) undefined
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