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A pseudoinverse learning algorithm for feedforward neural networks with stacked generalization applications to software reliability growth data
2004
Neurocomputing
A supervised learning algorithm, Pseudoinverse Learning Algorithm (PIL), for feedforward neural networks is developed. The algorithm is based on generalized linear algebraic methods, and it adopts matrix inner products and pseudoinverse operations. Incorporating with network architecture of which the number of hidden layer neuron is equal to the number of examples to be learned, the algorithm eliminates learning errors by adding hidden layers and will give an exact solution (perfect learning).
doi:10.1016/s0925-2312(03)00385-0
fatcat:fybj2vszcrf6nhpfounhrwkomi