Which of the following statements is not true about maximum margin?*1 pointc) If the location of the boundary is not perfect due to noise, this gives us the least chance of misclassificationd) It is not immune to removal of any non-support-vector data pointsa) It is safe and empirically works wellb) It is not sensitive to removal of any non support vector data points

Why is maximum margin hyperplane important in SVM?

What is a support vector in the context of support vector machines?Question 7Answera.A data point that is used to define the decision boundaryb.A data point that lies on the margin boundaryc.A data point that maximizes the margind.A data point that is classified correctly

What do you mean by a hard margin?Review LaterThe SVM allows high amount of error in classificationThe SVM allows very low error in classificationNone of the above

What is the meaning of “maximum margin hyperplanes”? and What are the characteristics of hyperplanes      that support vector machines learn from a training set?

In CVP analysis the margin of safety is the:Group of answer choicesnone of the options are true.excess of the break-even point over actual sales.excess of expected revenue above the break-even point.excess of the operating leverage above revenu