2.Question 2What is the objective of SVM in terms of hyperplanes?1 pointChoose the hyperplane that’s closest to one of the two classes.Minimize the distance between hyperplane and the support vectors.Find the hyperplane of the lowest dimension.Choose the hyperplane that represents the largest margin between the two classes.

the hyperplane having maximum distance from any support vectorthe hyperplane having minimum distance with the support vectorsthe hyperplane having maximum marginNone of the above

What is the objective of a Support Vector Machine (SVM)?Answer areaTo maximize the distance between the decision boundary and the nearest data points of any classTo minimize the number of misclassified pointsTo maximize the number of support vectorsTo minimize the computational complexity

Why is maximum margin hyperplane important in SVM?

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 machine learning, which algorithm is known for creating an optimal hyperplane to classify data points?Review LaterAdaBoost ClassifierRandom ForestSupport Vector Machine (SVM)K-Nearest Neighbors