SVM

 Going back to the AI lecture, got an introduction to the Support-Vector

Machine (SVM), a machine learning algorithm to classify data points or

find a linear solution. The idea is to arrive at a demarcation so that new data

can fit into one category or the other ie a classification, that can take the form

of a straight line or a higher dimensional form. Its adequacy is ensured by maximizing

the distance from individual data points.

No:

Yes:

Finding a higher dimension decision boundary:

So how does one choose between approaches for a problem ?! By seeing

how poorly our  model performs.