Data Science, Machine Learning, Algorithms, Support Vector Machine, Supervised Learning.
most real world problems, data is messy and it’s usually not completely separable. That’s why SVM shares an important characteristic with the algorithm that came before it, support vector classifiers. It allows the algorithm to make mistakes, and assign the wrong class to some vectors. Decision