# Getting the weights to compare AMORE NN models?

I'm using the AMORE NN package to build multiple models from the same training set and i want to compare the weights between the models.

I'm pretty much an R newbie, but some of the stronger R users I know can't answer either.

here's the code:

library("AMORE")
net <- newff(n.neurons=c(104,200,104), learning.rate.global=1e-2,
momentum.global=0.5,error.criterium="LMS", Stao=NA,
hidden.layer="tansig",output.layer="purelin",
result <- train(net, x, y, error.criterium="LMS",
report=TRUE, show.step=50, n.shows=20 )


net is pretty easy to break out into some functions and I think input weights.

net$neurons is where all the layer weights are. net$neurons is a or list of length 304. net$neurons[n] will print out what appears to be a set of units from the model. But it contains many things and I can't seem to get them out short of cut and paste. I won't paste it all here - my model is pretty big as you can see and it goes on for several pages, but just to give you an idea: net$neurons[1]

$type [1] "output"$activation.function

[1] 3

$output.links [1] NA$output.aims

[1] 103

$input.links [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 [19] 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 [37] 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 [55] 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 [73] 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 [91] 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 [109] 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 [127] 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 [145] 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 [163] 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 [181] 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 [199] 199 200$weights [1] 7.767180e-03 -5.118608e-03 4.683484e-03 6.499882e-03 6.897404e-04 [6] 4.169454e-03 -5.282092e-05 9.589098e-04 7.031523e-03 6.669872e-03 [11] 2.716605e-03 -4.188492e-04 -4.141848e-03 -6.576378e-03 -6.812882e-03 [16] -3.511420e-03 -3.091805e-04 7.128892e-03 7.160105e-03 -8.050284e-03 [21] 3.386642e-03 2.579751e-03 7.065484e-03 1.872059e-04 1.829110e-03 [26] 7.472301e-03 -8.303545e-03 7.981113e-03 3.584151e-03 -4.432509e-03 [31] -8.705997e-04 -7.456132e-03 -9.884449e-04 7.523373e-03 -6.673688e-03 [36] -9.070783e-04 3.068912e-03 -8.045977e-04 -2.165867e-03 5.507719e-03 ...

There's lots more, lots more, but it all has this general format.
Things that give no answer at all:

net$neuron[1]$weights
net$neuron[1,"weights"] net$neuron[1,1]
net$neuron[1]["weights"]  probably some of the above is laughably impossible anyway, but can anyone point me somewhere useful? thanks ## 1 Answer net$neuron[1][[1]][[7]]

first neuron, first list, element 7 are the weights

net\$neuron[1][[1]][[8]]

element 8 is the bias