This item signifies a perform that can take a data sample and jobs it into kernel function Place. The result is an actual valued column vector that signifies a degree in the kernel attribute Area. Scenarios of the item are designed utilizing the empirical_kernel_map.
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This object represents a radial foundation perform kernel to be used with kernel Understanding equipment that function on sparse vectors.
To make use of the empirical_kernel_map you provide it with a particular kernel plus a list of basis samples. After which you can existing it with new samples and it will venture them in the A part of kernel feature House spanned by your foundation samples.
This is a straightforward linear kmeans clustering implementation. It uses Euclidean distance to compare samples.
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This item provides N copies of the computational layer onto a deep neural network. It is basically similar to applying add_layer N moments, except that it includes significantly less typing, and for large N, will compile much faster.
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