Overview#
Hidden node (or hidden layer) contains one
neuron for each
classification in the
training dataset.
Hidden node stores the values of the predictor
variables for the
classification along with the target value. A Hidden node computes the Euclidean distance of the test case from the
neuron’s center point and then applies the radial basis function kernel function using the sigma values.
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