Why Do We Use Kernel In SVM? “Kernel” is used due to set of mathematical functions used in Support Vector Machine provides the window to manipulate the data. So, Kernel Function generally transforms the training set of data so that a non-linear decision surface is able to transformed to a linear equation in a higher
What Is RBF Kernel In SVM? RBF is the default kernel used within the sklearn’s SVM classification algorithm and can be described with the following formula: … The default value for gamma in sklearn’s SVM classification algorithm is: Briefly: ||x – x’||2 is the squared Euclidean distance between two feature vectors (2 points). Is RBF
What Is A Linear Kernel In SVM? Linear Kernel is used when the data is Linearly separable, that is, it can be separated using a single Line. It is one of the most common kernels to be used. It is mostly used when there are a Large number of Features in a particular Data Set.