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

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

When classifying images into tiger and lions, which image classification algorithm finds the best plane that divides a dataset into two classes?1 pointK-Nearest NeighboursLogistic RegressionSupport Vector MachinesK-Means

Support Vector Machines (SVM)Support Vector Machine (SVM) in 2 minutes by Visually ExplainedSupport Vector Machines Part 1 (of 3): Main Ideas!!! by StatQuest with Josh StarmerSupport Vector Machines: All you need to know! by Intuitive Machine LearningSupport Vector Machines: Dual formulation by Machine Learning- Sudeshna SarkarSupport Vector Machines (2): Dual & soft-margin forms by Alexander IhlerSVM: The Dual Formulation by Ashish KhistiSupport Vectors and Hyperplanes by Khan AcademySlack Variables by MathFAQLinear Programming 4: Slack/Surplus, Binding Constraints, Standard Form by Joshua EmmanuelIntroducing Slack Variables by WCSU MathLagrange Multipliers by The Organic Chemistry TutorLagrange Multipliers | Geometric Meaning & Full Example by Dr. Trefor BazettLagrange multipliers, using tangency to solve constrained optimization by Khan Academy

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

Which supervised learning algorithm is based on the idea of minimizing the sum of squared errors between the predicted and actual target values?Review LaterLinear regressionLogistic regressionK-nearest neighborsDecision tree