mirror of
https://github.com/ltcptgeneral/IdealRMT-DecisionTrees.git
synced 2025-09-04 14:27:23 +00:00
temp fix for issue with metadata
This commit is contained in:
@@ -37,36 +37,16 @@
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"execution_count": 3,
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"id": "12ad454d",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"here1\n",
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" protocl src dst classfication\n",
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"0 6 40234 5228 other\n",
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"1 6 40234 5228 other\n",
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"2 6 443 46330 Dropcam\n",
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"3 6 3063 443 other\n",
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"4 1 0 0 Netatmo Camera\n",
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"... ... ... ... ...\n",
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"2419339 6 443 47940 Dropcam\n",
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"2419340 6 47940 443 other\n",
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"2419341 6 443 47940 Dropcam\n",
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"2419342 0 0 0 iHome PowerPlug\n",
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"2419343 0 0 0 other\n",
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"\n",
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"[2419344 rows x 4 columns]\n",
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"{8, 20}\n",
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"{13}\n",
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"[6, 40234, 5228]\n",
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"other\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"predict_Yt = []\n",
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"index=0\n",
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"original_tree = open('tree.json', 'r')\n",
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"original_tree = json.load(original_tree)\n",
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"path_to_class = {}\n",
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"for i in range(len(original_tree[\"paths\"])):\n",
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" path = original_tree[\"paths\"][i]\n",
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" path_to_class[path[\"id\"]] = path[\"classification\"]\n",
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"with open('compressed_tree.json', 'r') as file:\n",
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" data = json.load(file)\n",
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" classes = data[\"classes\"]\n",
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@@ -105,28 +85,11 @@
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"\n",
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" #predict_Yt.append(list(result))\n",
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" #print(result)\n",
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" if len(result) == 1:\n",
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" prediction = list(result)[0]\n",
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" pred_class = classes[prediction]\n",
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" predict_Yt.append(pred_class)\n",
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" elif len(paths) == 1:\n",
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" print(\"here1\")\n",
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" print(pd.read_csv('data.csv'))\n",
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" print(result)\n",
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" print(paths)\n",
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" print(x)\n",
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" print(Y[index])\n",
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" break\n",
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" predict_Yt.append(None)\n",
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" else:\n",
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" print(\"here2\")\n",
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" print(pd.read_csv('data.csv'))\n",
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" print(result)\n",
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" print(paths)\n",
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" print(x)\n",
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" print(Y[index])\n",
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" break\n",
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" predict_Yt.append(None)\n",
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" assert len(paths) == 1\n",
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" path = list(paths)[0]\n",
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" pred = path_to_class[path]\n",
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" pred_class = classes[pred]\n",
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" predict_Yt.append(pred_class)\n",
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" \n",
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" index += 1"
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]
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@@ -138,14 +101,10 @@
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"metadata": {},
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"outputs": [
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{
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"ename": "IndexError",
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"evalue": "list index out of range",
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"output_type": "error",
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"traceback": [
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"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
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"\u001b[31mIndexError\u001b[39m Traceback (most recent call last)",
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"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m correct = \u001b[32m0\u001b[39m\n\u001b[32m 2\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(Y)):\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m prediction = \u001b[43mpredict_Yt\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m prediction != \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m Y[i] == prediction:\n\u001b[32m 5\u001b[39m correct += \u001b[32m1\u001b[39m\n",
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"\u001b[31mIndexError\u001b[39m: list index out of range"
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"0.8451332670948943\n"
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]
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}
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],
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