Open Access

Table 3

Comparison of ANNs performance with 11 different BPLAs to predict C DCM.

BPLA Function MSE × 103 R 2 Epochs
Resilient backpropagation Trainrp 0.47245 0.99672 2000
BFGS quasi-Newton backpropagation Trainbfg 0.11915 0.999 1900
Conjugate gradient backpropagation with Powell-Beale restarts Traincgb 0.19062 0.99847 777
Conjugate gradient backpropagation with Fletcher-Reeves updates Traincgf 0.44301 0.99723 308
Conjugate gradient backpropagation with Polak-Ribiere updates Traincgp 0.16445 0.9988 1275
Gradient descent with adaptive learning rate backpropagation Traingda 1.339 0.99103 4992
Gradient descent with momentum backpropagation Traingdm 9.0481 0.939 5000
Gradient descent with momentum and adaptive learning rate backpropagation Traingdx 0.78019 0.99426 5000
Levenberg-Marquardt backpropagation Trainlm 0.05714 6 0.99954 479
One-step secant backpropagation Trainoss 0.17262 0.99866 4008
Scaled conjugate gradient backpropagation Trainscg 0.11095 0.99921 4870

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.