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elisno committed Jan 17, 2024
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 53bf9165ae252f06cf47c722384f3dda
config: 23915d37363845cce4345d7e29f06c92
tags: 645f666f9bcd5a90fca523b33c5a78b7
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"dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n",
"\n",
"if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n",
" %pip install git+https://github.com/cleanlab/cleanlab.git@a8d2170f0db89b804931917dd930161c971bea94\n",
" %pip install git+https://github.com/cleanlab/cleanlab.git@15bec56103a268b4cbc829af93459cd8a66649de\n",
" cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
" %pip install $cmd\n",
"else:\n",
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" \n",
"\n",
"Number of examples with this issue: 6\n",
"Overall dataset quality in terms of this issue: 0.5221\n",
"Overall dataset quality in terms of this issue: 0.3558\n",
"\n",
"Examples representing most severe instances of this issue:\n",
" is_outlier_issue outlier_score\n",
"126 True 0.046465\n",
"130 True 0.068695\n",
"129 True 0.068695\n",
"127 True 0.076251\n",
"128 True 0.083941\n",
"126 True 0.006636\n",
"130 True 0.012571\n",
"129 True 0.012571\n",
"127 True 0.014909\n",
"128 True 0.017443\n",
"\n",
"\n",
"------------------ near_duplicate issues -------------------\n",
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"outputs": [
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" <tr>\n",
" <th>2</th>\n",
" <td>outlier</td>\n",
" <td>0.522080</td>\n",
" <td>0.355772</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
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" issue_type score num_issues\n",
"0 null 1.000000 0\n",
"1 label 0.856061 17\n",
"2 outlier 0.522080 6\n",
"2 outlier 0.355772 6\n",
"3 near_duplicate 0.616034 4\n",
"4 non_iid 0.821750 0\n",
"5 class_imbalance 0.022727 3"
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" <td>False</td>\n",
" <td>0.859109</td>\n",
" <td>False</td>\n",
" <td>0.586131</td>\n",
" <td>0.417707</td>\n",
" <td>False</td>\n",
" <td>0.664083</td>\n",
" <td>False</td>\n",
Expand All @@ -1120,7 +1120,7 @@
" <td>False</td>\n",
" <td>0.816965</td>\n",
" <td>False</td>\n",
" <td>0.548979</td>\n",
" <td>0.375317</td>\n",
" <td>False</td>\n",
" <td>0.641516</td>\n",
" <td>False</td>\n",
Expand All @@ -1135,7 +1135,7 @@
" <td>False</td>\n",
" <td>0.530924</td>\n",
" <td>False</td>\n",
" <td>0.622256</td>\n",
" <td>0.460593</td>\n",
" <td>False</td>\n",
" <td>0.601188</td>\n",
" <td>False</td>\n",
Expand All @@ -1150,7 +1150,7 @@
" <td>False</td>\n",
" <td>0.752776</td>\n",
" <td>False</td>\n",
" <td>0.499498</td>\n",
" <td>0.321635</td>\n",
" <td>False</td>\n",
" <td>0.562539</td>\n",
" <td>False</td>\n",
Expand All @@ -1165,7 +1165,7 @@
" <td>True</td>\n",
" <td>0.090224</td>\n",
" <td>False</td>\n",
" <td>0.632385</td>\n",
" <td>0.472909</td>\n",
" <td>False</td>\n",
" <td>0.746763</td>\n",
" <td>False</td>\n",
Expand All @@ -1186,11 +1186,11 @@
"4 False 1.0 True 0.090224 False \n",
"\n",
" outlier_score is_near_duplicate_issue near_duplicate_score \\\n",
"0 0.586131 False 0.664083 \n",
"1 0.548979 False 0.641516 \n",
"2 0.622256 False 0.601188 \n",
"3 0.499498 False 0.562539 \n",
"4 0.632385 False 0.746763 \n",
"0 0.417707 False 0.664083 \n",
"1 0.375317 False 0.641516 \n",
"2 0.460593 False 0.601188 \n",
"3 0.321635 False 0.562539 \n",
"4 0.472909 False 0.746763 \n",
"\n",
" is_non_iid_issue non_iid_score is_class_imbalance_issue \\\n",
"0 False 0.970324 False \n",
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"shell.execute_reply": "2024-01-16T18:15:10.601446Z"
"iopub.execute_input": "2024-01-17T17:46:37.653232Z",
"iopub.status.busy": "2024-01-17T17:46:37.653033Z",
"iopub.status.idle": "2024-01-17T17:46:37.664158Z",
"shell.execute_reply": "2024-01-17T17:46:37.663528Z"
}
},
"outputs": [
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