this data point for the dhoklas and this point for the cat glass these points are also known as support vectors which are defined as data points that the margin pushes up against all points that are close to the opposing glass so the algorithm basically implies that only support vectors are important whereas training examples are ignore an example of this is so that if we have in our case of a dog that loser cat or get that is chrome like a dog we want our classifier to look at the extremes and set our margins based on these support