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WebRadial Basis Function Networks (RBF) RBF networks have three layers: input layer, hidden layer and output layer. One neuron in the input layer corresponds to each predictor variable. With respects to categorical variables, n -1 neurons are used where n is the number of categories. Hidden layer has a variable number of neurons. WebMar 17, 2024 · RBF centers can be selected randomly from a set of data by using supervised learning, or they can be defined by using k-means clusters using unsupervised learning[1]. We take each input vector and feed it into each basis. Then, we do a simple weighted sum to get our approximated function value at the end. irish stout stain color
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