diff --git a/GAMA_AutoML_Tutorial.ipynb b/GAMA_AutoML_Tutorial.ipynb
index 9b90d1f2eb218cbc0794e17ac87836c9cc771e95..1cbb73063d9e8e2debac5f648ac4a6a201145848 100644
--- a/GAMA_AutoML_Tutorial.ipynb
+++ b/GAMA_AutoML_Tutorial.ipynb
@@ -26,6 +26,20 @@
"Image source: https://github.com/openml-labs/gama/raw/master/images/logos/Logo-With-Grey-Name-Transparent.png"
]
},
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "id": "481fae1c",
+ "metadata": {},
+ "source": [
+ "## View Documentation At:\n",
+ "* https://openml-labs.github.io/gama/master/\n",
+ "* https://github.com/openml-labs/gama\n",
+ "* https://openml-labs.github.io/gama/master/index.html\n",
+ "* https://openml-labs.github.io/gama/master/user_guide/index.html#dashboard\n",
+ "* https://openml-labs.github.io/gama/master/api/index.html"
+ ]
+ },
{
"cell_type": "markdown",
"id": "25258b82",
@@ -44,12 +58,14 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 4,
"id": "bded45a9",
"metadata": {},
"outputs": [],
"source": [
- "# pip install gama"
+ "# pip install gama\n",
+ "# *or*\n",
+ "# pip3 install gama "
]
},
{
@@ -88,7 +104,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 1,
"id": "00a14ad0",
"metadata": {},
"outputs": [],
@@ -170,21 +186,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Starting `fit` which will take roughly 3 minutes...\n"
- ]
- },
- {
- "ename": "IndexError",
- "evalue": "list index out of range",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_25136/719449767.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[0mautoml\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mGamaClassifier\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_total_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m180\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstore\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"nothing\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn_jobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 12\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Starting `fit` which will take roughly 3 minutes...\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 13\u001b[1;33m \u001b[0mautoml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 14\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 15\u001b[0m \u001b[0mlabel_predictions\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mautoml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32m~\\REPOS\\DataTools_Tutorial_Demo\\envs_gama\\lib\\site-packages\\gama\\GamaClassifier.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, x, y, *args, **kwargs)\u001b[0m\n\u001b[0;32m 132\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_label_encoder\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtransform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0my_\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 133\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_evaluation_library\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdetermine_sample_indices\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstratify\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 134\u001b[1;33m \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 135\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 136\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0m_encode_labels\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32m~\\REPOS\\DataTools_Tutorial_Demo\\envs_gama\\lib\\site-packages\\gama\\gama.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, x, y, warm_start)\u001b[0m\n\u001b[0;32m 537\u001b[0m )\n\u001b[0;32m 538\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_post_processing\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdynamic_defaults\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 539\u001b[1;33m self.model = self._post_processing.post_process(\n\u001b[0m\u001b[0;32m 540\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_x\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 541\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_y\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32m~\\REPOS\\DataTools_Tutorial_Demo\\envs_gama\\lib\\site-packages\\gama\\postprocessing\\best_fit.py\u001b[0m in \u001b[0;36mpost_process\u001b[1;34m(self, x, y, timeout, selection)\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mselection\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mList\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mIndividual\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 25\u001b[0m ) -> object:\n\u001b[1;32m---> 26\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_selected_individual\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mselection\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 27\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_selected_individual\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpipeline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 28\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mIndexError\u001b[0m: list index out of range"
+ "Starting `fit` which will take roughly 3 minutes...\n",
+ "accuracy: 0.951048951048951\n",
+ "log loss: 0.13989498044372267\n"
]
}
],
@@ -222,7 +226,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 2,
"id": "35f68b4c",
"metadata": {},
"outputs": [
@@ -230,20 +234,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Starting `fit` which will take roughly 3 minutes...\n"
- ]
- },
- {
- "ename": "IndexError",
- "evalue": "list index out of range",
- "output_type": "error",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)",
- "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_25136/3966760049.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m 9\u001b[0m \u001b[0mautoml\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mGamaRegressor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmax_total_time\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m180\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstore\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"nothing\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn_jobs\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 10\u001b[0m \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Starting `fit` which will take roughly 3 minutes...\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 11\u001b[1;33m \u001b[0mautoml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 13\u001b[0m \u001b[0mpredictions\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mautoml\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX_test\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32m~\\REPOS\\DataTools_Tutorial_Demo\\envs_gama\\lib\\site-packages\\gama\\gama.py\u001b[0m in \u001b[0;36mfit\u001b[1;34m(self, x, y, warm_start)\u001b[0m\n\u001b[0;32m 537\u001b[0m )\n\u001b[0;32m 538\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_post_processing\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdynamic_defaults\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 539\u001b[1;33m self.model = self._post_processing.post_process(\n\u001b[0m\u001b[0;32m 540\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_x\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 541\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_y\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;32m~\\REPOS\\DataTools_Tutorial_Demo\\envs_gama\\lib\\site-packages\\gama\\postprocessing\\best_fit.py\u001b[0m in \u001b[0;36mpost_process\u001b[1;34m(self, x, y, timeout, selection)\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSeries\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mfloat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mselection\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mList\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mIndividual\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 25\u001b[0m ) -> object:\n\u001b[1;32m---> 26\u001b[1;33m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_selected_individual\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mselection\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 27\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_selected_individual\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpipeline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 28\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
- "\u001b[1;31mIndexError\u001b[0m: list index out of range"
+ "Starting `fit` which will take roughly 3 minutes...\n",
+ "MSE: 17.566521076771657\n"
]
}
],
@@ -282,25 +274,6 @@
"\n"
]
},
- {
- "cell_type": "markdown",
- "id": "ffdabb07",
- "metadata": {},
- "source": [
- "## References"
- ]
- },
- {
- "cell_type": "markdown",
- "id": "500eb430",
- "metadata": {},
- "source": [
- "* https://github.com/openml-labs/gama\n",
- "* https://openml-labs.github.io/gama/master/index.html\n",
- "* https://openml-labs.github.io/gama/master/user_guide/index.html#dashboard\n",
- "* https://openml-labs.github.io/gama/master/api/index.html"
- ]
- },
{
"cell_type": "markdown",
"id": "e0a28b97",
@@ -312,7 +285,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3 (ipykernel)",
+ "display_name": "Python 3",
"language": "python",
"name": "python3"
},
@@ -326,7 +299,12 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.7"
+ "version": "3.10.0"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
+ }
}
},
"nbformat": 4,