Does the image is logistic regression or SVM, and why?
The straight dashed-line shows the typical decision line in logistic regression or any linear classifier. The dashed-circle shows the decision line from SVM. Obviously, since the data is not linearly separable in the original 2D feature space, if someone makes a higher dimension space by taking into account non-linear interaction of the original 2 features then they can discriminate between x and o data using a linear discriminator applied in higher dimensions. This shows the beauty of kernel methods that can make a linear yet high-dimensional (infinite dimensions indeed) problem from a non-linear low-dimensional problem (finite dimensions actually).