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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. 321) We can also compute the coefficient of linear regression with the help of an analytical method called Normal Equation.
Which of the following is/are true about Normal Equation?
1. We don't have to choose the learning rate
2. It becomes slow when number of features is very large
3. No need to iterate
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Q. 322) If two variables are correlated, is it necessary that they have a linear relationship?
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Q. 323) Which of the following option is true regarding Regression and Correlation ?Note: y is dependent variable and x is independent variable.
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Q. 324) Suppose you are using a Linear SVM classifier with 2 class classification
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Q. 325) If you remove the non-red circled points from the data, the decision boundary will change?
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Q. 326) When the C parameter is set to infinite, which of the following holds true?
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Q. 327) Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of its hyper parameter.What would happen when you use very large value of C(C->infinity)?
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Q. 328) SVM can solvelinearand non- linearproblems
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Q. 329) The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N the number of features) that distinctly classifies the data points.
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Q. 330) Hyperplanes are boundaries that help classify the data points.
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