Presentation_Rashmi
SLIDE 1 What is SVM? “Support Vector Machine” (SVM) is a supervised machine learning algorithm which can be used for both classification or regression challenges. However, it is mostly used in classification problems. SLIDE 2 how does it work ? Identify the right hyper-plane (Scenario-1): SLIDE3: Identify the right hyper-plane (Scenario-2): SLIDE4: Here, maximizing the distances between nearest data point (either class) and hyper-plane will help us to decide the right hyper-plane. This distance is called as Margin SLIDE5: Identify the right hyper-plane (Scenario-3): SLIDE6: Find the hyper-plane to segregate to classes SLIDE Cost function and Gradient Function In the SVM algorithm, we are looking to maximize the margin between the data points and the hyperplane. The loss function that helps maximize the margin is hinge loss. SLIDE Regularization The objective of the regularization parameter is to balance the margin maximizat...









































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