nnet
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@ -37,7 +37,7 @@
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"outputs": [],
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"source": [
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"# these are the functions we want to classify\n",
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"scalar = 10 # larger is harder\n",
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"scalar = 5 # larger is harder\n",
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"noise = Distributions.Normal(0, 0.05)\n",
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"\n",
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"# # problem #1... non-overlapping\n",
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@ -70,7 +70,7 @@
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"# pick the plotting limits\n",
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"lim = (-1,1)\n",
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"funcs = [f1, f2]\n",
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"n = 40\n",
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"n = 20\n",
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"gridx, gridy = gridxy(lim, n)\n",
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"# default(xlim = lim, ylim = lim)\n",
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"\n",
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@ -126,7 +126,7 @@
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"net = buildTanhClassificationNet(\n",
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" 2, # number of inputs\n",
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" 1, # number of outputs\n",
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" [100,100,2], # hidden layers structure\n",
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" [2,2,2,2,2,2], # hidden layers structure\n",
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" params = NetParams(gradientModel = gradientModel)\n",
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")"
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]
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