Data Science, Machine Learning, Algorithms, Support Vector Machine, Supervised Learning.
polynomial kernel. Accuracy of SVM model with linear kernel. So it turns out that for this problem a simpler model, an SVM with a linear kernel, was the best solution. Hope you enjoyed these examples, and that you got a better understanding of SVMs and what kinds of problems they can be applied to.