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Fix non-homogeneous array creation in snapshoot recording of training funciton #299

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Fix non-homogeneous array creation in snapshoot recording of training funciton #299

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5 changes: 3 additions & 2 deletions lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb
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Expand Up @@ -462,7 +462,8 @@
" neg_out = np.dot(negative_examples, weights) \n",
" pos_correct = (pos_out >= 0).sum() / float(pos_count)\n",
" neg_correct = (neg_out < 0).sum() / float(neg_count)\n",
" snapshots.append((np.copy(weights),(pos_correct+neg_correct)/2.0))\n",
" # make correction a list so it is homogeneous to weights list then numpy array accepts\n",
" snapshots.append((np.concatenate(weights),[(pos_correct+neg_correct)/2.0,0,0]))\n",
"\n",
" return np.array(snapshots)\n",
"\n",
Expand All @@ -476,7 +477,7 @@
" pylab.plot(np.arange(len(snapshots[:,1])), snapshots[:,1])\n",
" pylab.ylabel('Accuracy')\n",
" pylab.xlabel('Iteration')\n",
" pylab.plot(step, snapshots[step,1], \"bo\")\n",
" pylab.plot(step, snapshots[step,1][0], \"bo\")\n",
" pylab.show()\n",
"def pl1(step): plotit(pos_examples,neg_examples,snapshots,step)"
]
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