project task 3: implement some other evaluation measure
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"slide_type": "-"
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@ -126,7 +126,7 @@
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"0 0.949459 0.752487"
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]
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"execution_count": 4,
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"execution_count": 23,
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"output_type": "execute_result"
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 40,
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"outputs": [
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@ -162,7 +162,7 @@
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" [ 77, 313, 475, ..., 11, 591, 175]])"
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"execution_count": 5,
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"execution_count": 40,
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"output_type": "execute_result"
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@ -183,15 +183,15 @@
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 25,
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"metadata": {},
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"outputs": [],
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"source": [
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"def ranking_metrics(test_ui, reco, super_reactions=[], topK=10):\n",
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" \n",
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" nb_items=test_ui.shape[1]\n",
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" relevant_users, super_relevant_users, prec, rec, F_1, F_05, prec_super, rec_super, ndcg, mAP, MRR, LAUC, HR=\\\n",
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" 0,0,0,0,0,0,0,0,0,0,0,0,0\n",
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" relevant_users, super_relevant_users, prec, rec, F_1, F_05, prec_super, rec_super, ndcg, mAP, MRR, LAUC, HR, HR2=\\\n",
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" 0,0,0,0,0,0,0,0,0,0,0,0,0,0\n",
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" \n",
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" cg = (1.0 / np.log2(np.arange(2, topK + 2)))\n",
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" cg_sum = np.cumsum(cg)\n",
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@ -244,6 +244,7 @@
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" ((nb_items-nb_u_rated_items)*nb_u_rated_items)\n",
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" \n",
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" HR+=nb_user_successes>0\n",
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" HR2+=nb_user_successes>1\n",
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" \n",
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" \n",
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" result=[]\n",
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@ -258,6 +259,7 @@
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" result.append(('MRR', MRR/relevant_users))\n",
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" result.append(('LAUC', LAUC/relevant_users))\n",
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" result.append(('HR', HR/relevant_users))\n",
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" result.append(('HR2', HR2/relevant_users))\n",
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"\n",
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" df_result=(pd.DataFrame(list(zip(*result))[1])).T\n",
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" df_result.columns=list(zip(*result))[0]\n",
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 41,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"text": [
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"943it [00:00, 11673.30it/s]\n"
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"943it [00:00, 9975.21it/s]\n"
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]
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@ -308,6 +310,7 @@
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" <th>MRR</th>\n",
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" <th>LAUC</th>\n",
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" <th>HR</th>\n",
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" <th>HR2</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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@ -324,6 +327,7 @@
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" <td>0.198193</td>\n",
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" <td>0.515501</td>\n",
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" <td>0.437964</td>\n",
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" <td>0.239661</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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@ -333,11 +337,11 @@
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" precision recall F_1 F_05 precision_super recall_super \\\n",
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"0 0.09141 0.037652 0.04603 0.061286 0.079614 0.056463 \n",
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"\n",
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" NDCG mAP MRR LAUC HR \n",
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"0 0.095957 0.043178 0.198193 0.515501 0.437964 "
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" NDCG mAP MRR LAUC HR HR2 \n",
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"0 0.095957 0.043178 0.198193 0.515501 0.437964 0.239661 "
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]
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},
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"execution_count": 7,
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"execution_count": 41,
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"metadata": {},
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"output_type": "execute_result"
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 27,
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"outputs": [],
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"source": [
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 28,
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"metadata": {},
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"outputs": [
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{
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@ -445,7 +449,7 @@
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"0 1.0 0.033911 2.836513 0.991139"
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]
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},
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"execution_count": 9,
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"execution_count": 28,
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"0 0.437964 1.0 0.033911 2.836513 0.991139 "
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"execution_count": 10,
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"0 0.000463 0.000644 0.000189 "
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"execution_count": 12,
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"outputs": [
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{
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"0 0.600530 0.005051 1.803126 0.996380 "
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"execution_count": 13,
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"text": [
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"3it [00:00, 3005.95it/s]\n"
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@ -1306,148 +1310,148 @@
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>24578</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>One Flew Over the Cuckoo's Nest (1975)</td>\n",
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" <td>Drama</td>\n",
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" <th>38020</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Beauty and the Beast (1991)</td>\n",
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" <td>Animation, Children's, Musical</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>12760</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Dances with Wolves (1990)</td>\n",
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" <td>Adventure, Drama, Western</td>\n",
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" <th>55943</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Room with a View, A (1986)</td>\n",
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" <td>Drama, Romance</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>43866</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Pulp Fiction (1994)</td>\n",
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" <td>Crime, Drama</td>\n",
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" <th>28786</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Cinderella (1950)</td>\n",
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" <td>Animation, Children's, Musical</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>37331</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Contact (1997)</td>\n",
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" <td>Drama, Sci-Fi</td>\n",
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" <th>24330</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Muppet Treasure Island (1996)</td>\n",
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" <td>Action, Adventure, Comedy, Musical, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>36057</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Silence of the Lambs, The (1991)</td>\n",
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" <td>Drama, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>31838</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Shawshank Redemption, The (1994)</td>\n",
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" <td>Drama</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>67376</th>\n",
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" <td>163</td>\n",
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" <td>4</td>\n",
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" <td>Good Will Hunting (1997)</td>\n",
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" <td>Drama</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>21714</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>In & Out (1997)</td>\n",
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" <td>Comedy</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>22153</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>Groundhog Day (1993)</td>\n",
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" <td>Comedy, Romance</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>19155</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>Scream (1996)</td>\n",
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" <td>Horror, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>26457</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>Air Force One (1997)</td>\n",
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" <td>Action, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>17924</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>English Patient, The (1996)</td>\n",
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" <th>23632</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Casablanca (1942)</td>\n",
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" <td>Drama, Romance, War</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16410</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>Apollo 13 (1995)</td>\n",
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" <td>Action, Drama, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>38849</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <th>39028</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Full Monty, The (1997)</td>\n",
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" <td>Comedy</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3992</th>\n",
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" <td>163</td>\n",
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" <td>3</td>\n",
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" <td>G.I. Jane (1997)</td>\n",
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" <td>Action, Drama, War</td>\n",
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" <th>21591</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>In & Out (1997)</td>\n",
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" <td>Comedy</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>20177</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Return of the Jedi (1983)</td>\n",
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" <td>Action, Adventure, Romance, Sci-Fi, War</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>19460</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Searching for Bobby Fischer (1993)</td>\n",
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" <td>Drama</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>16345</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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" <td>Apollo 13 (1995)</td>\n",
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" <td>Action, Drama, Thriller</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>15044</th>\n",
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" <td>751</td>\n",
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" <td>5</td>\n",
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||||
" <td>Indiana Jones and the Last Crusade (1989)</td>\n",
|
||||
" <td>Action, Adventure</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>28596</th>\n",
|
||||
" <td>751</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Right Stuff, The (1983)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>54274</th>\n",
|
||||
" <td>751</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>12 Angry Men (1957)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>10317</th>\n",
|
||||
" <td>751</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Breakfast at Tiffany's (1961)</td>\n",
|
||||
" <td>Drama, Romance</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>27371</th>\n",
|
||||
" <td>751</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Empire Strikes Back, The (1980)</td>\n",
|
||||
" <td>Action, Adventure, Drama, Romance, Sci-Fi, War</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" user rating title \\\n",
|
||||
"24578 163 4 One Flew Over the Cuckoo's Nest (1975) \n",
|
||||
"12760 163 4 Dances with Wolves (1990) \n",
|
||||
"43866 163 4 Pulp Fiction (1994) \n",
|
||||
"37331 163 4 Contact (1997) \n",
|
||||
"36057 163 4 Silence of the Lambs, The (1991) \n",
|
||||
"31838 163 4 Shawshank Redemption, The (1994) \n",
|
||||
"67376 163 4 Good Will Hunting (1997) \n",
|
||||
"21714 163 3 In & Out (1997) \n",
|
||||
"22153 163 3 Groundhog Day (1993) \n",
|
||||
"19155 163 3 Scream (1996) \n",
|
||||
"26457 163 3 Air Force One (1997) \n",
|
||||
"17924 163 3 English Patient, The (1996) \n",
|
||||
"16410 163 3 Apollo 13 (1995) \n",
|
||||
"38849 163 3 Full Monty, The (1997) \n",
|
||||
"3992 163 3 G.I. Jane (1997) \n",
|
||||
" user rating title \\\n",
|
||||
"38020 751 5 Beauty and the Beast (1991) \n",
|
||||
"55943 751 5 Room with a View, A (1986) \n",
|
||||
"28786 751 5 Cinderella (1950) \n",
|
||||
"24330 751 5 Muppet Treasure Island (1996) \n",
|
||||
"23632 751 5 Casablanca (1942) \n",
|
||||
"39028 751 5 Full Monty, The (1997) \n",
|
||||
"21591 751 5 In & Out (1997) \n",
|
||||
"20177 751 5 Return of the Jedi (1983) \n",
|
||||
"19460 751 5 Searching for Bobby Fischer (1993) \n",
|
||||
"16345 751 5 Apollo 13 (1995) \n",
|
||||
"15044 751 5 Indiana Jones and the Last Crusade (1989) \n",
|
||||
"28596 751 5 Right Stuff, The (1983) \n",
|
||||
"54274 751 5 12 Angry Men (1957) \n",
|
||||
"10317 751 5 Breakfast at Tiffany's (1961) \n",
|
||||
"27371 751 5 Empire Strikes Back, The (1980) \n",
|
||||
"\n",
|
||||
" genres \n",
|
||||
"24578 Drama \n",
|
||||
"12760 Adventure, Drama, Western \n",
|
||||
"43866 Crime, Drama \n",
|
||||
"37331 Drama, Sci-Fi \n",
|
||||
"36057 Drama, Thriller \n",
|
||||
"31838 Drama \n",
|
||||
"67376 Drama \n",
|
||||
"21714 Comedy \n",
|
||||
"22153 Comedy, Romance \n",
|
||||
"19155 Horror, Thriller \n",
|
||||
"26457 Action, Thriller \n",
|
||||
"17924 Drama, Romance, War \n",
|
||||
"16410 Action, Drama, Thriller \n",
|
||||
"38849 Comedy \n",
|
||||
"3992 Action, Drama, War "
|
||||
" genres \n",
|
||||
"38020 Animation, Children's, Musical \n",
|
||||
"55943 Drama, Romance \n",
|
||||
"28786 Animation, Children's, Musical \n",
|
||||
"24330 Action, Adventure, Comedy, Musical, Thriller \n",
|
||||
"23632 Drama, Romance, War \n",
|
||||
"39028 Comedy \n",
|
||||
"21591 Comedy \n",
|
||||
"20177 Action, Adventure, Romance, Sci-Fi, War \n",
|
||||
"19460 Drama \n",
|
||||
"16345 Action, Drama, Thriller \n",
|
||||
"15044 Action, Adventure \n",
|
||||
"28596 Drama \n",
|
||||
"54274 Drama \n",
|
||||
"10317 Drama, Romance \n",
|
||||
"27371 Action, Adventure, Drama, Romance, Sci-Fi, War "
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@ -1489,71 +1493,71 @@
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>161</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>749</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>Great Day in Harlem, A (1994)</td>\n",
|
||||
" <td>Documentary</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>1104</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>1691</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>2</td>\n",
|
||||
" <td>Tough and Deadly (1995)</td>\n",
|
||||
" <td>Action, Drama, Thriller</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2046</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>2633</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>3</td>\n",
|
||||
" <td>Aiqing wansui (1994)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>2988</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>3575</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>4</td>\n",
|
||||
" <td>Delta of Venus (1994)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3930</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>4517</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>Someone Else's America (1995)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>4872</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>5459</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>6</td>\n",
|
||||
" <td>Saint of Fort Washington, The (1993)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>5813</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>6401</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>7</td>\n",
|
||||
" <td>Celestial Clockwork (1994)</td>\n",
|
||||
" <td>Comedy</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>6756</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>7342</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>8</td>\n",
|
||||
" <td>Some Mother's Son (1996)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>8650</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>9238</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>9</td>\n",
|
||||
" <td>Maya Lin: A Strong Clear Vision (1994)</td>\n",
|
||||
" <td>Documentary</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>7696</th>\n",
|
||||
" <td>163.0</td>\n",
|
||||
" <th>8284</th>\n",
|
||||
" <td>751.0</td>\n",
|
||||
" <td>10</td>\n",
|
||||
" <td>Prefontaine (1997)</td>\n",
|
||||
" <td>Drama</td>\n",
|
||||
@ -1564,31 +1568,31 @@
|
||||
],
|
||||
"text/plain": [
|
||||
" user rec_nb title \\\n",
|
||||
"161 163.0 1 Great Day in Harlem, A (1994) \n",
|
||||
"1104 163.0 2 Tough and Deadly (1995) \n",
|
||||
"2046 163.0 3 Aiqing wansui (1994) \n",
|
||||
"2988 163.0 4 Delta of Venus (1994) \n",
|
||||
"3930 163.0 5 Someone Else's America (1995) \n",
|
||||
"4872 163.0 6 Saint of Fort Washington, The (1993) \n",
|
||||
"5813 163.0 7 Celestial Clockwork (1994) \n",
|
||||
"6756 163.0 8 Some Mother's Son (1996) \n",
|
||||
"8650 163.0 9 Maya Lin: A Strong Clear Vision (1994) \n",
|
||||
"7696 163.0 10 Prefontaine (1997) \n",
|
||||
"749 751.0 1 Great Day in Harlem, A (1994) \n",
|
||||
"1691 751.0 2 Tough and Deadly (1995) \n",
|
||||
"2633 751.0 3 Aiqing wansui (1994) \n",
|
||||
"3575 751.0 4 Delta of Venus (1994) \n",
|
||||
"4517 751.0 5 Someone Else's America (1995) \n",
|
||||
"5459 751.0 6 Saint of Fort Washington, The (1993) \n",
|
||||
"6401 751.0 7 Celestial Clockwork (1994) \n",
|
||||
"7342 751.0 8 Some Mother's Son (1996) \n",
|
||||
"9238 751.0 9 Maya Lin: A Strong Clear Vision (1994) \n",
|
||||
"8284 751.0 10 Prefontaine (1997) \n",
|
||||
"\n",
|
||||
" genres \n",
|
||||
"161 Documentary \n",
|
||||
"1104 Action, Drama, Thriller \n",
|
||||
"2046 Drama \n",
|
||||
"2988 Drama \n",
|
||||
"3930 Drama \n",
|
||||
"4872 Drama \n",
|
||||
"5813 Comedy \n",
|
||||
"6756 Drama \n",
|
||||
"8650 Documentary \n",
|
||||
"7696 Drama "
|
||||
"749 Documentary \n",
|
||||
"1691 Action, Drama, Thriller \n",
|
||||
"2633 Drama \n",
|
||||
"3575 Drama \n",
|
||||
"4517 Drama \n",
|
||||
"5459 Drama \n",
|
||||
"6401 Comedy \n",
|
||||
"7342 Drama \n",
|
||||
"9238 Documentary \n",
|
||||
"8284 Drama "
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"execution_count": 35,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -1636,32 +1640,37 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 16,
|
||||
"execution_count": 36,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# it may be your idea, modification of what we have already implemented \n",
|
||||
"# (for example Hit2 rate which would count as a success users whoreceived at least 2 relevant recommendations) \n",
|
||||
"# or something well-known\n",
|
||||
"# expected output: modification of evaluation_measures.py such that evaluate_all will also display your measure"
|
||||
"# expected output: modification of evaluation_measures.py such that evaluate_all will also display your measure\n",
|
||||
"\n",
|
||||
"#ROZWIĄZANIE:\n",
|
||||
"# Implementacja Hit2 rate w definicji funkcji ranking_metrics"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 17,
|
||||
"metadata": {},
|
||||
"execution_count": 44,
|
||||
"metadata": {
|
||||
"scrolled": true
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"943it [00:00, 11530.77it/s]\n",
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|
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|
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{
|
||||
@ -1886,7 +1895,7 @@
|
||||
"0 0.496424 0.009544 0.600530 0.005051 1.803126 0.996380 "
|
||||
]
|
||||
},
|
||||
"execution_count": 17,
|
||||
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|
||||
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|
||||
"output_type": "execute_result"
|
||||
}
|
||||
@ -1898,6 +1907,109 @@
|
||||
"\n",
|
||||
"ev.evaluate_all(test, dir_path, super_reactions)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 43,
|
||||
"metadata": {
|
||||
"scrolled": true
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"943it [00:00, 11668.03it/s]\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/html": [
|
||||
"<div>\n",
|
||||
"<style scoped>\n",
|
||||
" .dataframe tbody tr th:only-of-type {\n",
|
||||
" vertical-align: middle;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe tbody tr th {\n",
|
||||
" vertical-align: top;\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" .dataframe thead th {\n",
|
||||
" text-align: right;\n",
|
||||
" }\n",
|
||||
"</style>\n",
|
||||
"<table border=\"1\" class=\"dataframe\">\n",
|
||||
" <thead>\n",
|
||||
" <tr style=\"text-align: right;\">\n",
|
||||
" <th></th>\n",
|
||||
" <th>precision</th>\n",
|
||||
" <th>recall</th>\n",
|
||||
" <th>F_1</th>\n",
|
||||
" <th>F_05</th>\n",
|
||||
" <th>precision_super</th>\n",
|
||||
" <th>recall_super</th>\n",
|
||||
" <th>NDCG</th>\n",
|
||||
" <th>mAP</th>\n",
|
||||
" <th>MRR</th>\n",
|
||||
" <th>LAUC</th>\n",
|
||||
" <th>HR</th>\n",
|
||||
" <th>HR2</th>\n",
|
||||
" </tr>\n",
|
||||
" </thead>\n",
|
||||
" <tbody>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>0.09141</td>\n",
|
||||
" <td>0.037652</td>\n",
|
||||
" <td>0.04603</td>\n",
|
||||
" <td>0.061286</td>\n",
|
||||
" <td>0.079614</td>\n",
|
||||
" <td>0.056463</td>\n",
|
||||
" <td>0.095957</td>\n",
|
||||
" <td>0.043178</td>\n",
|
||||
" <td>0.198193</td>\n",
|
||||
" <td>0.515501</td>\n",
|
||||
" <td>0.437964</td>\n",
|
||||
" <td>0.239661</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" precision recall F_1 F_05 precision_super recall_super \\\n",
|
||||
"0 0.09141 0.037652 0.04603 0.061286 0.079614 0.056463 \n",
|
||||
"\n",
|
||||
" NDCG mAP MRR LAUC HR HR2 \n",
|
||||
"0 0.095957 0.043178 0.198193 0.515501 0.437964 0.239661 "
|
||||
]
|
||||
},
|
||||
"execution_count": 43,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"reco = np.loadtxt('Recommendations generated/ml-100k/Ready_Baseline_reco.csv', delimiter=',')\n",
|
||||
"# Let's ignore scores - they are not used in evaluation: \n",
|
||||
"users=reco[:,:1]\n",
|
||||
"items=reco[:,1::2]\n",
|
||||
"# Let's use inner ids instead of real ones\n",
|
||||
"users=np.vectorize(lambda x: user_id_code.setdefault(x, -1))(users)\n",
|
||||
"items=np.vectorize(lambda x: item_id_code.setdefault(x, -1))(items) # maybe items we recommend are not in test set\n",
|
||||
"# Let's put them into one array\n",
|
||||
"reco=np.concatenate((users, items), axis=1)\n",
|
||||
"\n",
|
||||
"ranking_metrics(test_ui, reco, super_reactions=[4,5], topK=10)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user