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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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