COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Gaussian kernel function
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Polynomial kernel function
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Sigmiod kernel function
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Linear kernel function
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Detailed explanation-1: -Popular kernels are: Polynomial Kernel, Gaussian Kernel, Radial Basis Function (RBF), Laplace RBF Kernel, Sigmoid Kernel, Anove RBF Kernel, etc (see Kernel Functions or a more detailed description Machine Learning Kernels).
Detailed explanation-2: -RBF is the most popular support vector machine kernel choice, and the default one used in sklearn . RBF is short for “radial basis function", a type of function that is used to approximate other functions in the literature.
Detailed explanation-3: -“Kernel” is used due to a set of mathematical functions used in Support Vector Machine providing 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 transform to a linear equation in a higher number of dimension spaces.
Detailed explanation-4: -The linear kernel is typically used on data sets with large amounts of features as increasing the dimensionality on these data set does not necessarily improve separability. Text classification is a typical example of this kind of data set.