Data Science, Machine Learning, Algorithms, Support Vector Machine, Supervised Learning.
error. Support vector machines SVMs share the characteristics of the margin classifiers that came before it. What is unique about them is how they can define both linear and non-linear decision boundaries. To support non-linear decision boundaries, SMVs use functions to transform the original