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Nonlinear transfer functions (like hyperbolic tangents) in the hidden layers empower the network to characterize arbitrary continuous curves. 2. Principal Curves and Manifolds
To accomplish this, three primary methodologies have emerged over the decades: 1. Autoassociative Neural Networks (Autoencoders) Nonlinear Principal Component Analysis and Rela...
Because the bottleneck layer contains fewer nodes than the input or output layers, the network is forced to compress the data. The values extracted at this bottleneck represent the nonlinear principal component scores. Nonlinear Principal Component Analysis and Rela...
