Two Dimensional Stochastic Configuration Networks for Image Data Analytics

6 Sep 2018Ming LiDianhui Wang

Stochastic configuration networks (SCNs) as a class of randomized learner model have been successfully employed in data analytics due to its universal approximation capability and fast modelling property. The technical essence lies in stochastically configuring hidden nodes (or basis functions) based on a supervisory mechanism rather than data-independent randomization as usually adopted for building randomized neural networks... (read more)

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