Feature Map

Creator
Creator
Seonglae Cho
Created
Created
2023 Apr 17 7:47
Editor
Edited
Edited
2025 May 20 22:43
Refs
Refs
Kernel

Vector to vector ϕ(x)\phi(x)

A function that maps input data into a high-dimensional feature space
When data is mapped nonlinearly, it takes on nonlinear forms in 3D space, making it possible to classify well even with linear classifiers
Similarly, the kernel function result is the inner product between Feature Maps of x and z
A feature map is a function that sends data to a feature space. While in practice we only need to calculate kernel values, we analyze the dimensionality of kernels like RBF (which despite simple calculations can map to infinite dimensions through Fourier analysis) for theoretical understanding. This helps us understand the model's complexity, which is why feature map dimensional analysis is necessary.
 
 
 
 
 
 

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