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Found 4 papers, 0 papers with code
Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification
This re-normalization method can help the network avoid divergence of the hidden features.
Stacked Autoencoder Based Deep Random Vector Functional Link Neural Network for Classification
Specifically, we introduce direct connections (feature reuse) from preceding layers to the fore layers of the network as in the original RVFL network.
Random Vector Functional Link Neural Network based Ensemble Deep Learning
The parameters of the hidden layers of the dRVFL are randomly generated within a suitable range and kept fixed while the output weights are computed using the closed form solution as in a standard RVFL network.
Enhancing Multi-Class Classification of Random Forest using Random Vector Functional Neural Network and Oblique Decision Surfaces
In this paper, we first present a new variant of oblique decision tree based on a linear classifier, then construct an ensemble classifier based on the fusion of a fast neural network, random vector functional link network and oblique decision trees.
