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dl/xai.ipynb

Lines changed: 2 additions & 2 deletions
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"from myst_nb import glue\n",
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"\n",
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"val = []\n",
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"ms = np.linspace(2, 512, 25)\n",
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"ms = np.linspace(2, 1024, 25)\n",
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"for m in ms.astype(np.int32):\n",
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" sampled_x = train_x[:m]\n",
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" val.append(\n",
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"source": [
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"As someone who works with peptides, I believe the Shapley values are the most accurate here. Shapley values tend to give a smoother, more balanced view of feature importance than raw gradients.\n",
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"\n",
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"What can we conclude from this information? We could perhaps add an explanation like this: \"The sequence is predicted to be hemolytic primarily because of the tryptophan (W), tyrosine (Y), and lack of glycine (G).\"\n",
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"What can we conclude from this information? We could perhaps add an explanation like this: \"The sequence is predicted to be hemolytic primarily because of the tryptophan (W) and tyrosine (Y) residues.\"\n",
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"\n",
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"## What is feature importance for?\n",
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"\n",

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