Radial Basis Function (RBF)

The Radial Basis Function (RBF) uses a single non-linear hidden layer known as a "Feature Vector," with the hidden layer having more neurons than the input layer to transform the data into a higher-dimensional space. This higher dimensionality makes the classification more separable in a high-dimensional space. The inputs () are transformed to output () using the single hidden layer (feature vector) which connects to x and y through the weights.