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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
Coach

Q. 601) The adjusted multiple coefficient of determination accounts for

(A) the number of dependent variables in the model
(B) the number of independent variables in the model
(C) unusually large predictors
(D) none of the above
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Mr. Dubey • 51.17K Points
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Q. 602) The multiple coefficient of determination is computed by

(A) dividing ssr by sst
(B) dividing sst by ssr
(C) dividing sst by sse
(D) none of the above
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Mr. Dubey • 51.17K Points
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Q. 603) For a multiple regression model, SST = 200 and SSE = 50. The multiple coefficient of determination is

(A) 0.25
(B) 4.00
(C) 0.75
(D) none of the above
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Mr. Dubey • 51.17K Points
Coach

Q. 604) A nearest neighbor approach is best used

(A) with large-sized datasets.
(B) when irrelevant attributes have been removed from the data.
(C) when a generalized model of the data is desirable.
(D) when an explanation of what has been found is of primary importance.
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Mr. Dubey • 51.17K Points
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Q. 605) Another name for an output attribute.

(A) predictive variable
(B) independent variable
(C) estimated variable
(D) dependent variable
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Mr. Dubey • 51.17K Points
Coach

Q. 606) Classification problems are distinguished from estimation problems in that

(A) classification problems require the output attribute to be numeric.
(B) classification problems require the output attribute to be categorical.
(C) classification problems do not allow an output attribute.
(D) classification problems are designed to predict future outcome.
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Mr. Dubey • 51.17K Points
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Q. 607) Which statement is true about prediction problems?

(A) the output attribute must be categorical.
(B) the output attribute must be numeric.
(C) the resultant model is designed to determine future outcomes.
(D) the resultant model is designed to classify current behavior.
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Mr. Dubey • 51.17K Points
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Q. 608) Which of the following is a common use of unsupervised clustering?

(A) detect outliers
(B) determine a best set of input attributes for supervised learning
(C) evaluate the likely performance of a supervised learner model
(D) determine if meaningful relationships can be found in a dataset
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Mr. Dubey • 51.17K Points
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Q. 609) The average positive difference between computed and desired outcome values.

(A) root mean squared error
(B) mean squared error
(C) mean absolute error
(D) mean positive error
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Mr. Dubey • 51.17K Points
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Q. 610) Selecting data so as to assure that each class is properly represented in both the training and test set.

(A) cross validation
(B) stratification
(C) verification
(D) bootstrapping
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