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elisno committed Jan 22, 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: c85cf038e16935d8219fd92dcbf182c0
config: 7c1eebdb633c1423ff706327bc15dffe
tags: 645f666f9bcd5a90fca523b33c5a78b7
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"execution_count": 1,
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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@7504a21cf72e3f15699b7c8f82261100fdad4175\n",
" %pip install git+https://github.com/cleanlab/cleanlab.git@3910f0d955a5e4e8b5e5d7c831efeb8522cf172a\n",
" cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n",
" %pip install $cmd\n",
"else:\n",
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"execution_count": 10,
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"outputs": [
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"\n",
"Examples representing most severe instances of this issue:\n",
" is_label_issue label_score given_label predicted_label\n",
"77 False 0.001894 max mid\n",
"58 False 0.003565 max high\n",
"8 False 0.007326 max mid\n",
"7 True 0.008974 low mid\n",
"120 True 0.009699 high mid\n",
"77 False 0.001908 max mid\n",
"58 False 0.003564 max high\n",
"8 False 0.007331 max mid\n",
"7 True 0.008963 low mid\n",
"120 True 0.009664 high mid\n",
"\n",
"\n",
"---------------------- outlier issues ----------------------\n",
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"execution_count": 12,
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"outputs": [
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" <td>False</td>\n",
" <td>1.0</td>\n",
" <td>False</td>\n",
" <td>0.859109</td>\n",
" <td>0.859131</td>\n",
" <td>False</td>\n",
" <td>0.417707</td>\n",
" <td>False</td>\n",
Expand All @@ -1118,7 +1118,7 @@
" <td>False</td>\n",
" <td>1.0</td>\n",
" <td>False</td>\n",
" <td>0.816965</td>\n",
" <td>0.816953</td>\n",
" <td>False</td>\n",
" <td>0.375317</td>\n",
" <td>False</td>\n",
Expand All @@ -1133,7 +1133,7 @@
" <td>False</td>\n",
" <td>1.0</td>\n",
" <td>False</td>\n",
" <td>0.530924</td>\n",
" <td>0.531021</td>\n",
" <td>False</td>\n",
" <td>0.460593</td>\n",
" <td>False</td>\n",
Expand All @@ -1148,7 +1148,7 @@
" <td>False</td>\n",
" <td>1.0</td>\n",
" <td>False</td>\n",
" <td>0.752776</td>\n",
" <td>0.752808</td>\n",
" <td>False</td>\n",
" <td>0.321635</td>\n",
" <td>False</td>\n",
Expand All @@ -1163,7 +1163,7 @@
" <td>False</td>\n",
" <td>1.0</td>\n",
" <td>True</td>\n",
" <td>0.090224</td>\n",
" <td>0.090243</td>\n",
" <td>False</td>\n",
" <td>0.472909</td>\n",
" <td>False</td>\n",
Expand All @@ -1179,11 +1179,11 @@
],
"text/plain": [
" is_null_issue null_score is_label_issue label_score is_outlier_issue \\\n",
"0 False 1.0 False 0.859109 False \n",
"1 False 1.0 False 0.816965 False \n",
"2 False 1.0 False 0.530924 False \n",
"3 False 1.0 False 0.752776 False \n",
"4 False 1.0 True 0.090224 False \n",
"0 False 1.0 False 0.859131 False \n",
"1 False 1.0 False 0.816953 False \n",
"2 False 1.0 False 0.531021 False \n",
"3 False 1.0 False 0.752808 False \n",
"4 False 1.0 True 0.090243 False \n",
"\n",
" outlier_score is_near_duplicate_issue near_duplicate_score \\\n",
"0 0.417707 False 0.664083 \n",
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Expand Down Expand Up @@ -1269,35 +1269,35 @@
" <tr>\n",
" <th>7</th>\n",
" <td>True</td>\n",
" <td>0.008974</td>\n",
" <td>0.008963</td>\n",
" <td>low</td>\n",
" <td>mid</td>\n",
" </tr>\n",
" <tr>\n",
" <th>120</th>\n",
" <td>True</td>\n",
" <td>0.009699</td>\n",
" <td>0.009664</td>\n",
" <td>high</td>\n",
" <td>mid</td>\n",
" </tr>\n",
" <tr>\n",
" <th>40</th>\n",
" <td>True</td>\n",
" <td>0.013444</td>\n",
" <td>0.013445</td>\n",
" <td>mid</td>\n",
" <td>low</td>\n",
" </tr>\n",
" <tr>\n",
" <th>107</th>\n",
" <td>True</td>\n",
" <td>0.025173</td>\n",
" <td>0.025184</td>\n",
" <td>high</td>\n",
" <td>mid</td>\n",
" </tr>\n",
" <tr>\n",
" <th>53</th>\n",
" <td>True</td>\n",
" <td>0.026416</td>\n",
" <td>0.026376</td>\n",
" <td>high</td>\n",
" <td>mid</td>\n",
" </tr>\n",
Expand All @@ -1307,11 +1307,11 @@
],
"text/plain": [
" is_label_issue label_score given_label predicted_label\n",
"7 True 0.008974 low mid\n",
"120 True 0.009699 high mid\n",
"40 True 0.013444 mid low\n",
"107 True 0.025173 high mid\n",
"53 True 0.026416 high mid"
"7 True 0.008963 low mid\n",
"120 True 0.009664 high mid\n",
"40 True 0.013445 mid low\n",
"107 True 0.025184 high mid\n",
"53 True 0.026376 high mid"
]
},
"execution_count": 14,
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"execution_count": 15,
"metadata": {
"execution": {
"iopub.execute_input": "2024-01-19T15:45:58.524277Z",
"iopub.status.busy": "2024-01-19T15:45:58.524085Z",
"iopub.status.idle": "2024-01-19T15:45:58.531464Z",
"shell.execute_reply": "2024-01-19T15:45:58.530937Z"
"iopub.execute_input": "2024-01-22T16:10:56.196673Z",
"iopub.status.busy": "2024-01-22T16:10:56.196234Z",
"iopub.status.idle": "2024-01-22T16:10:56.203835Z",
"shell.execute_reply": "2024-01-22T16:10:56.203215Z"
},
"scrolled": true
},
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"execution_count": 16,
"metadata": {
"execution": {
"iopub.execute_input": "2024-01-19T15:45:58.533829Z",
"iopub.status.busy": "2024-01-19T15:45:58.533487Z",
"iopub.status.idle": "2024-01-19T15:45:58.543317Z",
"shell.execute_reply": "2024-01-19T15:45:58.542691Z"
"iopub.execute_input": "2024-01-22T16:10:56.206242Z",
"iopub.status.busy": "2024-01-22T16:10:56.205773Z",
"iopub.status.idle": "2024-01-22T16:10:56.215854Z",
"shell.execute_reply": "2024-01-22T16:10:56.215231Z"
}
},
"outputs": [
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