Question

17. What is not true about using a support vector machine (SVM) algorithm to solve a classification problem? A: The choice of the kernel influences the performance of an SVM model. B: SVM finds decision boundaries that separate the classes with large distances (margin). O C: The loss function of SVM is convex and has a global minimum. D: SVM is not suited for finding nonlinear decision boundaries.​

Answer 1

Answer:

here is ur answer

Explanation:

In this article,

1. you will learn about SVM or Support Vector Machine,
2. which is one of the most popular AI algorithms (it’s one of the top 10 AI algorithms) and about the Kernel Trick,
3. which deals with non-linearity and higher dimensions.
4. We will touch topics like hyperplanes, Lagrange Multipliers,