Update tabular_data_supervised_learning_using_automl.ipynb

Author: Neha Sharma

samples/04_gis_analysts_data_scientists/tabular_data_supervised_learning_using_automl.ipynb

@@ -106,7 +106,7 @@
        "                        </a>\n",
        "                        <br/><br/><img src='https://geosaurus.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\" width=16 height=16>Feature Layer Collection by api_data_owner\n",
        "                        <br/>Last Modified: October 23, 2020\n",
-       "                        <br/>0 comments, 11,806 views\n",
+       "                        <br/>0 comments, 11,832 views\n",
        "                    </div>\n",
        "                </div>\n",
        "                "
@@ -344,7 +344,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = prepare_tabulardata(calgary_no_southland_solar_layer_sdf,\n",
+    "data = prepare_tabulardata(calgary_no_southland_solar_layer,\n",
     "                           'capacity_f',\n",
     "                           explanatory_variables=X,                           \n",
     "                           preprocessors=preprocessors)"
@@ -439,27 +439,27 @@
      "output_type": "stream",
      "text": [
       "Neural Network algorithm was disabled because it doesn't support n_jobs parameter.\n",
-      "AutoML directory: C:\\Users\\Neh13173\\AppData\\Local\\Temp\\scratch\\tmpbbocurt8\n",
+      "AutoML directory: ~\\AppData\\Local\\Temp\\scratch\\tmpmbhb97_l\n",
       "The task is regression with evaluation metric rmse\n",
       "AutoML will use algorithms: ['Linear', 'Decision Tree', 'Random Trees', 'Extra Trees', 'LightGBM', 'Xgboost']\n",
       "AutoML will ensemble available models\n",
       "AutoML steps: ['simple_algorithms', 'default_algorithms', 'ensemble']\n",
       "* Step simple_algorithms will try to check up to 2 models\n",
-      "1_DecisionTree rmse 0.048893 trained in 2.82 seconds\n",
+      "1_DecisionTree rmse 0.048893 trained in 3.63 seconds\n",
       "Exception while producing SHAP explanations. 'float' object has no attribute 'shape'\n",
       "Continuing ...\n",
-      "2_Linear rmse 0.046288 trained in 0.88 seconds\n",
+      "2_Linear rmse 0.046288 trained in 1.1 seconds\n",
       "* Step default_algorithms will try to check up to 4 models\n",
-      "3_Default_LightGBM rmse 0.028985 trained in 6.61 seconds\n",
+      "3_Default_LightGBM rmse 0.028985 trained in 7.23 seconds\n",
       "There was an error during 4_Default_Xgboost training.\n",
-      "Please check C:\\Users\\Neh13173\\AppData\\Local\\Temp\\scratch\\tmpbbocurt8\\errors.md for details.\n",
-      "5_Default_RandomTrees rmse 0.043642 trained in 3.75 seconds\n",
-      "6_Default_ExtraTrees rmse 0.044894 trained in 5.79 seconds\n",
+      "Please check ~\\AppData\\Local\\Temp\\scratch\\tmpmbhb97_l\\errors.md for details.\n",
+      "5_Default_RandomTrees rmse 0.043642 trained in 4.5 seconds\n",
+      "6_Default_ExtraTrees rmse 0.044894 trained in 6.55 seconds\n",
       "* Step ensemble will try to check up to 1 model\n",
-      "Ensemble rmse 0.028985 trained in 0.2 seconds\n",
-      "AutoML fit time: 27.25 seconds\n",
+      "Ensemble rmse 0.028985 trained in 0.28 seconds\n",
+      "AutoML fit time: 32.35 seconds\n",
       "AutoML best model: 3_Default_LightGBM\n",
-      "All the evaluated models are saved in the path  C:\\Users\\Neh13173\\AppData\\Local\\Temp\\scratch\\tmpbbocurt8\n"
+      "All the evaluated models are saved in the path  ~\\AppData\\Local\\Temp\\scratch\\tmpmbhb97_l\n"
      ]
     }
    ],
@@ -902,6 +902,7 @@
    "metadata": {
     "scrolled": true
    },
+   "outputs": [],
    "source": [
     "AutoML_class_obj.report()"
    ]