Main Loop
for (dset in names(NNdatasets)) {
##Â =============================================
##Â EXTRACT INFORMATION FROM THE SELECTED DATASET
##Â =============================================
ds <- NNdatasets[[dset]]$ds
Z <- NNdatasets[[dset]]$Z
neur <- NNdatasets[[dset]]$neur
nparNN <- NNdatasets[[dset]]$nparNN
fmlaNN <- NNdatasets[[dset]]$fmlaNN
donotremove <- c("dset", "dsets", "ds", "Z", "neur", "TF", "nrep", "timer",
"donotremove", "donotremove2")
donotremove2 <- c("dset", "dsets")
##Â ===================================================
## SELECT THE FORMAT REQUIRED BY THE PACKAGE/ALGORITHM
## d = data.frame, m = matrix, v = vector/numeric
##Â ATTACH THE OBJECTS CREATED (x, y, Zxy, ... )
## ===================================================
ZZ <- prepareZZ(Z, xdmv = "m", ydmv = "v", zdm = "d", scale = TRUE)
attach(ZZ)
##Â =============================================
##Â SELECT THE PACKAGE USED FOR TRAINING
## nrep => SELECT THE NUMBER OF INDEPENDANT RUNS
##Â iter => SELECT THE MAX NUMBER OF ITERATIONS
##Â TF => PLOT THE RESULTS
##Â =============================================
nrep <- 10
TF <- TRUE
method <- c("gaussNewton")
for (m in method) {
descr <- paste(dset, "brnn::brnn", m, sep = "_")
##Â AUTO
Ypred <- list()
Rmse <- numeric(length = nrep)
Mae <- numeric(length = nrep)
for(i in 1:nrep){
event <- paste0(descr, sprintf("_%.2d", i))
timer$start(event)
#### ADJUST THE FOLLOWING LINES TO THE PACKAGE::ALGORITHM
hyper_params <- hyperParams(optim_method = m)
NNreg <- tryCatch(
NNtrain(x = x, y = y, hidden_neur = neur, optim_method = m),
error = function(y) {lm(y ~ 0, data = Zxy)}
)
y_pred <- tryCatch(
ym0 + ysd0 * predict(NNreg, x),
error = ym0
)
####
Ypred[[i]] <- y_pred
Rmse[i] <- funRMSE(y_pred, y0)
Mae[i] <- funMAE(y_pred, y0)
timer$stop(event, RMSE = Rmse[i], MAE = Mae[i], params = hyper_params$params, printmsg = FALSE)
}
best <- which(Rmse == min(Rmse, na.rm = TRUE))[1]
best ; Rmse[[best]]
## ================================================
##Â PLOT ALL MODELS AND THE MODEL WITH THE BEST RMSE
##Â par OPTIONS CAN BE IMPROVED FOR A BETTER DISPLAY
## ================================================
op <- par(mfcol = c(1,2))
plotNN(xory, y0, uni, TF, main = descr)
for (i in 1:nrep) lipoNN(xory, Ypred[[i]], uni, TF, col = i, lwd = 1)
plotNN(xory, y0, uni, TF, main = descr)
lipoNN(xory, Ypred[[best]], uni, TF, col = 4, lwd = 4)
par(op)
}
##Â ===========================
## DETACH ZZ - END OF THE LOOP
##Â ===========================
detach(ZZ)
}
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 24.6526 alpha= 0.0186 beta= 351.1388
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 23.7098 alpha= 0.0826 beta= 8.8596
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 23.6435 alpha= 0.03 beta= 11.6588
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 24.6593 alpha= 0.0182 beta= 354.662
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 23.7956 alpha= 0.0449 beta= 10.8747
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 19.6799 alpha= 0.1265 beta= 6.9923
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 21.8089 alpha= 0.1219 beta= 7.3302
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 23.7478 alpha= 0.0855 beta= 8.7187
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 23.7142 alpha= 0.0896 beta= 8.6295
## Number of parameters (weights and biases) to estimate: 25
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 21.6862 alpha= 0.1111 beta= 7.4059
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.6333 alpha= 0.1295 beta= 160.6423
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.468 alpha= 0.0343 beta= 445.8517
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.6337 alpha= 0.1303 beta= 161.0038
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.6392 alpha= 0.1244 beta= 167.533
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.4348 alpha= 0.0299 beta= 483.9497
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.6257 alpha= 0.1289 beta= 162.3004
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.4367 alpha= 0.0301 beta= 482.4449
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.4586 alpha= 0.0311 beta= 477.0961
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.4438 alpha= 0.0074 beta= 657.4524
## Number of parameters (weights and biases) to estimate: 35
## Nguyen-Widrow method
## Scaling factor= 0.7022568
## gamma= 34.6326 alpha= 0.1371 beta= 151.1164
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 45.6373 alpha= 0.1098 beta= 13.8367
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 46.1694 alpha= 0.1022 beta= 13.7693
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 24.8253 alpha= 0.3588 beta= 0.9666
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 45.0981 alpha= 0.1017 beta= 13.8904
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 45.9287 alpha= 0.0979 beta= 11.0922
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 23.8185 alpha= 0.3408 beta= 0.959
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 44.4714 alpha= 0.1122 beta= 12.2016
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 44.3894 alpha= 0.0992 beta= 14.1057
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 26.0789 alpha= 0.3749 beta= 0.9599
## Number of parameters (weights and biases) to estimate: 50
## Nguyen-Widrow method
## Scaling factor= 0.7032311
## gamma= 45.4778 alpha= 0.09 beta= 14.1824
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.1948 alpha= 0.9969 beta= 28.3033
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 18.9029 alpha= 0.9587 beta= 29.2725
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.3305 alpha= 0.9155 beta= 30.6316
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.3905 alpha= 0.8705 beta= 29.1605
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.3295 alpha= 0.9159 beta= 30.6296
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.1981 alpha= 0.9955 beta= 28.3088
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 18.7037 alpha= 1.3276 beta= 26.4416
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 18.9033 alpha= 0.9583 beta= 29.2744
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 18.7002 alpha= 1.328 beta= 26.4404
## Number of parameters (weights and biases) to estimate: 21
## Nguyen-Widrow method
## Scaling factor= 0.7050444
## gamma= 19.3286 alpha= 0.9165 beta= 30.6263
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 0 alpha= 64.0625 beta= 0.51
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 5.6608 alpha= 0.0969 beta= 1.3445
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.5656 alpha= 0.0243 beta= 58.5773
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.1902 alpha= 0.0277 beta= 39.8655
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 0.4596 alpha= 4.2933 beta= 0.5094
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.5607 alpha= 0.0242 beta= 58.6795
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 0 alpha= 33.4877 beta= 0.51
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.5654 alpha= 0.0243 beta= 58.5858
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.5612 alpha= 0.0242 beta= 58.6779
## Number of parameters (weights and biases) to estimate: 18
## Nguyen-Widrow method
## Scaling factor= 4.2
## gamma= 16.5655 alpha= 0.0243 beta= 58.5739
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.857 alpha= 0.0301 beta= 52.6607
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 5.5399 alpha= 0.0779 beta= 1.6145
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 12.5786 alpha= 0.026 beta= 23.2944
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 5.5256 alpha= 0.0805 beta= 1.602
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 11.5633 alpha= 0.0346 beta= 16.4319
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 5.6265 alpha= 0.0792 beta= 1.6126
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 12.9036 alpha= 0.0271 beta= 22.9985
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 12.8854 alpha= 0.027 beta= 23.0225
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 11.1847 alpha= 0.041 beta= 12.3873
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 11.3702 alpha= 0.036 beta= 15.662
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9926 alpha= 0.0622 beta= 219677.3
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9857 alpha= 0.0778 beta= 2313.577
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9879 alpha= 0.0632 beta= 10139.56
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9756 alpha= 0.0631 beta= 88471.8
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9484 alpha= 0.0646 beta= 8827.237
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.989 alpha= 0.0625 beta= 65583.79
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9833 alpha= 0.0627 beta= 78019.69
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.988 alpha= 0.0634 beta= 6627.03
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.987 alpha= 0.0627 beta= 49814.43
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.9755 alpha= 0.0632 beta= 53701.76
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 9
## Nguyen-Widrow method
## Scaling factor= 2.1
## gamma= 8.8506 alpha= 0.0675 beta= 130.7886
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.0702 alpha= 0.0216 beta= 113.4521
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.4964 alpha= 0.0258 beta= 112.2635
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 14.7659 alpha= 0.0436 beta= 161.2961
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 14.7659 alpha= 0.0436 beta= 161.2961
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.666 alpha= 0.0357 beta= 160.259
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.6354 alpha= 0.0263 beta= 121.5528
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 14.3008 alpha= 0.0311 beta= 162.9315
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.8289 alpha= 0.0114 beta= 17.7978
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 13.3009 alpha= 0.0183 beta= 141.0345
## Number of parameters (weights and biases) to estimate: 15
## Nguyen-Widrow method
## Scaling factor= 3.5
## gamma= 14.7659 alpha= 0.0436 beta= 161.2961
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.5691 alpha= 0.0324 beta= 108.7706
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6723 alpha= 0.0272 beta= 117.9975
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6549 alpha= 0.0305 beta= 114.7937
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6362 alpha= 0.0257 beta= 118.7185
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 10.4216 alpha= 0.0037 beta= 45.4168
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 10.4951 alpha= 0.0046 beta= 44.1352
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6802 alpha= 0.0283 beta= 117.307
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6639 alpha= 0.0302 beta= 115.3709
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6046 alpha= 0.0247 beta= 119.133
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.3222 alpha= 0.0339 beta= 101.7393
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.8754 alpha= 0.0481 beta= 96.029
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.7208 alpha= 0.0458 beta= 101.8855
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6896 alpha= 0.0483 beta= 75.1771
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.8754 alpha= 0.0481 beta= 96.0291
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.1364 alpha= 0.0546 beta= 123.8739
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.8754 alpha= 0.0481 beta= 96.029
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.7763 alpha= 0.0367 beta= 124.1513
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6896 alpha= 0.0483 beta= 75.1766
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.6897 alpha= 0.0483 beta= 75.1764
## Number of parameters (weights and biases) to estimate: 12
## Nguyen-Widrow method
## Scaling factor= 2.8
## gamma= 11.7763 alpha= 0.0367 beta= 124.1513
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0814 beta= 5.9026
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7328 alpha= 0.0813 beta= 5.903
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0814 beta= 5.9026
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0814 beta= 5.9027
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7328 alpha= 0.0814 beta= 5.9028
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0813 beta= 5.9031
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7328 alpha= 0.0814 beta= 5.9025
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7326 alpha= 0.0813 beta= 5.903
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0814 beta= 5.9025
## Number of parameters (weights and biases) to estimate: 6
## Nguyen-Widrow method
## Scaling factor= 1.4
## gamma= 5.7327 alpha= 0.0813 beta= 5.903