Data Science, Machine Learning, Algorithms, Support Vector Machine, Supervised Learning.
Classification based on where the vector falls, respective to the decision boundary. If you are working with more than two dimensions, as in, your feature vector X has more than two features, you’re classifying vectors, instead of points. So, to generalize, all vectors that fall below the decision