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Name and describe three different kernel functions and in what situation you would use each.
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Name and describe three different kernel functions and in what situation you would use each...
Answer / Ranbir
1. Linear Kernel: This is the simplest kernel function, where it calculates the dot product of vectors. It's used when the data can be linearly separated or for finding similarities between vectors. n2. Polynomial Kernel (Polynomial degree p): It maps the original input space into a higher dimensional feature space to better separate non-linearly separable data. n3. Gaussian RBF Kernel: This kernel function defines a Gaussian distribution around each training point, measuring similarity based on distance. It's widely used in Support Vector Machines (SVM) due to its ability to handle complex and noisy data.
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