What is a kernel? Explain the kernel trick

Data Science, AI and ML
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#1

What is a kernel? Explain the kernel trick

#2

The idea is mapping the non-linear separable data-set into a higher dimensional space where we can find a hyperplane that can separate the samples.
Popular kernels are: Polynomial Kernel, Gaussian Kernel, Radial Basis Function (RBF), Laplace RBF Kernel, Sigmoid Kernel, Anove RBF Kernel , etc

#3

The “Kernel Trick” is a term that occurs in the machine learning domain. It is widely used in the Support Vector Machine model (SVM), specifically for bridging linearity and non-linearity. For the understanding kernel, we need to first understand SVM.

The SVM model mainly relates to supervised machine learning, that is used for classifications. Precisely, for separating different groups with the help of decision boundaries.

The significance of Kernel trick is that it helps in mapping data, to higher dimensions.