RBFSampler# class sklearn.kernel_approximation.RBFSampler(*, gamma=1.0, n_components=100, random_state=None)[source]# Approximate a RBF kernel feature map using random Fourier features. It implements a variant of Random Kitchen Sinks.[1] Read more in the User Guide. Parameters: gamma‘scale’ or float, default=1.0Parameter of RBF kernel: exp(-gamma * x^2). If gamma='scale' is passed then it uses 1 /