Machine Learning, Svm, Support Vector Machine, Data Science, Kernel.
The second line stays as far away as possible from both the clusters while getting the training data separation right. By being right in the middle of the two clusters, it is less “risky,” gives the data distributions for each class some wiggle room so to speak, and thus generalizes well on test