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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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Q. 361) Problem:Players will play if weather is sunny. Is this statement is correct?
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Q. 362) For the given weather data, Calculate probability of not playing
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Q. 363) Suppose you have trained an SVM with linear decision boundary after training SVM, you correctly infer that your SVM model is under fitting.Which of the following option would you more likely to consider iterating SVM next time?
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Q. 364) The minimum time complexity for training an SVM is O(n2). According to this fact, what sizes of datasets are not best suited for SVMs?
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Q. 365) What do you mean by generalization error in terms of the SVM?
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Q. 366) We usually use feature normalization before using the Gaussian kernel in SVM. What is true about feature normalization?
1.We do feature normalization so that new feature will dominate other
2. Some times, feature normalization is not feasible in case of categorical variables
3. Feature normalization always helps when we use Gaussian kernel in SVM
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Q. 367) Support vectors are the data points that lie closest to the decision surface.
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Q. 368) Suppose you are given ‘n’ predictions on test data by ‘n’ different models (M1, M2, …. Mn) respectively. Which of the following method(s) can be used to combine the predictions of these models?
Note: We are working on a regression problem
1. Median
2. Product
3. Average
4. Weighted sum
5. Minimum and Maximum
6. Generalized mean rule
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Q. 369) In an election, N candidates are competing against each other and people are voting for either of the candidates. Voters don’t communicate with each other while casting their votes. Which of the following ensemble method works similar to above-discussed election procedure? Hint: Persons are like base models of ensemble method.
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Q. 370) Which of the following is NOT supervised learning?
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