Different kernels in SVM
There are four types of kernels in SVM. Linear Kernel Polynomial kernel Radial basis kernel Sigmoid kernel
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SVM algorithm
SVM stands for support vector machine, it is a supervised machine learning algorithm which can be used for both Regression and Classification. If you have n features in your training data set, SVM tries to plot it in n-dimensional space with the value of each feature being the value of a particular coordinate. SVM uses hyperplanes to separate out different classes based on the provided kernel function.