mirror of
https://github.com/20kaushik02/CSE515_MWDB_Project.git
synced 2025-12-06 07:54:07 +00:00
201 lines
8.0 KiB
Plaintext
201 lines
8.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"from utils import *\n",
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"warnings.filterwarnings('ignore')\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"fd_collection = getCollection(\"team_5_mwdb_phase_2\", \"fd_collection\")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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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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"Applying svd on the cm_fd space to get 10 latent semantics (showing only top 10 image-weight pairs for each latent semantic)...\n",
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"Latent semantic no. 0\n",
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"Image_ID\t7654\t-\tWeight\t0.08162189274964751\n",
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"Image_ID\t8634\t-\tWeight\t0.06673589485778451\n",
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"Image_ID\t5740\t-\tWeight\t0.060058821201972104\n",
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"Image_ID\t6106\t-\tWeight\t0.05306661393931607\n",
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"Image_ID\t5456\t-\tWeight\t0.05170171570330845\n",
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"Image_ID\t7814\t-\tWeight\t0.04997978865116185\n",
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"Image_ID\t6248\t-\tWeight\t0.04946683639815072\n",
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"Image_ID\t5354\t-\tWeight\t0.04864381025793171\n",
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"Image_ID\t6108\t-\tWeight\t0.04796763934338538\n",
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"Image_ID\t5438\t-\tWeight\t0.047874747600689466\n",
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"Latent semantic no. 1\n",
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"Image_ID\t8026\t-\tWeight\t0.06478360955460367\n",
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"Image_ID\t6016\t-\tWeight\t0.0632709906607753\n",
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"Image_ID\t3744\t-\tWeight\t0.05347414608321652\n",
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"Image_ID\t3720\t-\tWeight\t0.0517124023583583\n",
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"Image_ID\t7896\t-\tWeight\t0.049366978424645006\n",
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"Image_ID\t6014\t-\tWeight\t0.047637173390389816\n",
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"Image_ID\t6768\t-\tWeight\t0.04742408995375774\n",
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"Image_ID\t4050\t-\tWeight\t0.0456343920101654\n",
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"Image_ID\t6000\t-\tWeight\t0.04535273415975713\n",
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"Image_ID\t6552\t-\tWeight\t0.04525300117499444\n",
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"Latent semantic no. 2\n",
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"Image_ID\t7654\t-\tWeight\t0.0704670166327785\n",
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"Image_ID\t2804\t-\tWeight\t0.059682344110996065\n",
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"Image_ID\t2710\t-\tWeight\t0.059199111598090534\n",
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"Image_ID\t3436\t-\tWeight\t0.05368202357324355\n",
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"Image_ID\t7936\t-\tWeight\t0.053276991496894154\n",
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"Image_ID\t2708\t-\tWeight\t0.048527019795007204\n",
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"Image_ID\t3764\t-\tWeight\t0.04835537239641643\n",
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"Image_ID\t7928\t-\tWeight\t0.047998989024259496\n",
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"Image_ID\t5684\t-\tWeight\t0.04723047448150771\n",
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"Image_ID\t5126\t-\tWeight\t0.04720498270016634\n",
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"Latent semantic no. 3\n",
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"Image_ID\t6356\t-\tWeight\t0.0754447261688377\n",
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"Image_ID\t6480\t-\tWeight\t0.06540890240964665\n",
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"Image_ID\t4756\t-\tWeight\t0.06075370676621832\n",
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"Image_ID\t8656\t-\tWeight\t0.060505116069252685\n",
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"Image_ID\t6050\t-\tWeight\t0.058111632773274836\n",
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"Image_ID\t6324\t-\tWeight\t0.056492568599917435\n",
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"Image_ID\t8138\t-\tWeight\t0.0557967464751822\n",
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"Image_ID\t3460\t-\tWeight\t0.05508818833516222\n",
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"Image_ID\t200\t-\tWeight\t0.05459477384213874\n",
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"Image_ID\t7220\t-\tWeight\t0.05376222500332758\n",
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"Latent semantic no. 4\n",
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"Image_ID\t7370\t-\tWeight\t0.05281026462493995\n",
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"Image_ID\t6528\t-\tWeight\t0.05252803707219332\n",
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"Image_ID\t8056\t-\tWeight\t0.05175019567880743\n",
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"Image_ID\t2958\t-\tWeight\t0.05123118911737749\n",
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"Image_ID\t4614\t-\tWeight\t0.05061302210733273\n",
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"Image_ID\t8292\t-\tWeight\t0.05000577057549489\n",
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"Image_ID\t7888\t-\tWeight\t0.04905059301012787\n",
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"Image_ID\t6540\t-\tWeight\t0.048139958875035395\n",
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"Image_ID\t6064\t-\tWeight\t0.04605896293857696\n",
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"Image_ID\t2974\t-\tWeight\t0.04488429099909397\n",
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"Latent semantic no. 5\n",
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"Image_ID\t8570\t-\tWeight\t0.08379938013632145\n",
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"Image_ID\t7784\t-\tWeight\t0.0723847258804912\n",
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"Image_ID\t4152\t-\tWeight\t0.060769224719766333\n",
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"Image_ID\t5114\t-\tWeight\t0.053872121517690504\n",
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"Image_ID\t7774\t-\tWeight\t0.05324887247523992\n",
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"Image_ID\t8614\t-\tWeight\t0.05319742868629013\n",
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"Image_ID\t3072\t-\tWeight\t0.05083994521792821\n",
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"Image_ID\t7798\t-\tWeight\t0.05059807413594892\n",
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"Image_ID\t5118\t-\tWeight\t0.05022770477320976\n",
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"Image_ID\t7040\t-\tWeight\t0.04996996742218053\n",
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"Latent semantic no. 6\n",
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"Image_ID\t8570\t-\tWeight\t0.07082421149695754\n",
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"Image_ID\t7774\t-\tWeight\t0.06546594547486781\n",
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"Image_ID\t4152\t-\tWeight\t0.06440870014673936\n",
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"Image_ID\t5118\t-\tWeight\t0.06264436903974217\n",
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"Image_ID\t7784\t-\tWeight\t0.06203552824772956\n",
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"Image_ID\t7798\t-\tWeight\t0.05899354962287134\n",
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"Image_ID\t7896\t-\tWeight\t0.05648444493570963\n",
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"Image_ID\t7766\t-\tWeight\t0.056063042928801675\n",
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"Image_ID\t7792\t-\tWeight\t0.055578803018497686\n",
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"Image_ID\t7834\t-\tWeight\t0.055567509183302555\n",
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"Latent semantic no. 7\n",
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"Image_ID\t7912\t-\tWeight\t0.06634864556518678\n",
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"Image_ID\t5534\t-\tWeight\t0.05913926717735747\n",
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"Image_ID\t5550\t-\tWeight\t0.049468125695492526\n",
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"Image_ID\t2106\t-\tWeight\t0.048274676516220805\n",
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"Image_ID\t7804\t-\tWeight\t0.04822832951751611\n",
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"Image_ID\t6198\t-\tWeight\t0.04795521082538372\n",
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"Image_ID\t6728\t-\tWeight\t0.04729135404469566\n",
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"Image_ID\t5588\t-\tWeight\t0.04715637083533252\n",
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"Image_ID\t7276\t-\tWeight\t0.04637482601331893\n",
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"Image_ID\t6730\t-\tWeight\t0.045930617636659\n",
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"Latent semantic no. 8\n",
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"Image_ID\t1798\t-\tWeight\t0.04586412291217343\n",
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"Image_ID\t1802\t-\tWeight\t0.044772142290101236\n",
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"Image_ID\t1806\t-\tWeight\t0.044448676280621977\n",
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"Image_ID\t1202\t-\tWeight\t0.043679466488681935\n",
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"Image_ID\t1786\t-\tWeight\t0.04351371229636818\n",
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"Image_ID\t1784\t-\tWeight\t0.04346765741634348\n",
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"Image_ID\t1790\t-\tWeight\t0.04288750664761761\n",
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"Image_ID\t1642\t-\tWeight\t0.041863484069841805\n",
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"Image_ID\t1788\t-\tWeight\t0.04089406629514228\n",
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"Image_ID\t1796\t-\tWeight\t0.04068815222347919\n",
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"Latent semantic no. 9\n",
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"Image_ID\t8582\t-\tWeight\t0.02577153311253718\n",
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"Image_ID\t8612\t-\tWeight\t0.025608143819276445\n",
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"Image_ID\t7290\t-\tWeight\t0.025578071187110543\n",
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"Image_ID\t7298\t-\tWeight\t0.025350467801040884\n",
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"Image_ID\t7302\t-\tWeight\t0.02531661140938117\n",
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"Image_ID\t7318\t-\tWeight\t0.025212779767014252\n",
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"Image_ID\t8580\t-\tWeight\t0.025201323062899284\n",
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"Image_ID\t6392\t-\tWeight\t0.02517086205642468\n",
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"Image_ID\t2738\t-\tWeight\t0.025106516897995135\n",
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"Image_ID\t6420\t-\tWeight\t0.02510499876667641\n"
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]
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}
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],
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"source": [
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"selected_feature_model = valid_feature_models[\n",
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" str(input(\"Enter feature model - one of \" + str(list(valid_feature_models.keys()))))\n",
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"]\n",
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"\n",
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"k = int(input(\"Enter value of k: \"))\n",
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"if k < 1:\n",
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" raise ValueError(\"k should be a positive integer\")\n",
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"\n",
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"selected_dim_reduction_method = str(\n",
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" input(\n",
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" \"Enter dimensionality reduction method - one of \"\n",
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" + str(list(valid_dim_reduction_methods.keys()))\n",
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" )\n",
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")\n",
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"\n",
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"extract_latent_semantics(\n",
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" fd_collection,\n",
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" k,\n",
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" selected_feature_model,\n",
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" selected_dim_reduction_method,\n",
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" top_images=10,\n",
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")\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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