fix ga

Author: Rpan4853

notebooks/modeling.ipynb

@@ -545,9 +545,13 @@
           "text": [
             "/Users/raymondpan/zephyr/Zephyr-repo/venv/lib/python3.8/site-packages/sklearn/impute/_base.py:555: UserWarning: Skipping features without any observed values: [ 1  2  6  7  9 10 15 16 17 18]. At least one non-missing value is needed for imputation with strategy='mean'.\n",
             "  warnings.warn(\n",
-            "[GUIDE] Successfully performed set_feature_matrix.\n",
+            "[GUIDE] STALE WARNING: set_feature_matrix.\n",
+            "\tPerforming step 2 with set_feature_matrix.\n",
+            "\tThis is a forward step via a set method.\n",
+            "\tAll previous steps' results will be considered stale.\n",
+            "[GUIDE] DONE: set_feature_matrix.\n",
             "\tYou can perform the next step by calling generate_train_test_split.\n",
-            "[GUIDE] Successfully performed generate_train_test_split.\n",
+            "[GUIDE] DONE: generate_train_test_split.\n",
             "\tYou can perform the next step by calling fit_pipeline.\n"
           ]
         },
@@ -604,7 +608,16 @@
       "execution_count": 3,
       "id": "edffee03",
       "metadata": {},
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "[GUIDE] DONE: fit_pipeline.\n",
+            "\tYou can perform the next step by calling predict or evaluate.\n"
+          ]
+        }
+      ],
       "source": [
         "hyperparameters = {\n",
         "    \"xgboost.XGBClassifier#1\": {\n",
@@ -629,6 +642,15 @@
       "id": "78187756",
       "metadata": {},
       "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "[GUIDE] DONE: predict.\n",
+            "\tYou have reached the end of the predictive engineering workflow.\n",
+            "\tYou can call predict or evaluate again or re-perform previous steps based on results.\n"
+          ]
+        },
         {
           "data": {
             "text/plain": [
@@ -644,6 +666,14 @@
         "zephyr.predict()"
       ]
     },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "0c8440ee",
+      "metadata": {},
+      "outputs": [],
+      "source": []
+    },
     {
       "cell_type": "markdown",
       "id": "24cda971",
@@ -657,7 +687,17 @@
       "execution_count": 5,
       "id": "cd097853",
       "metadata": {},
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "[GUIDE] DONE: evaluate.\n",
+            "\tYou have reached the end of the predictive engineering workflow.\n",
+            "\tYou can call predict or evaluate again or re-perform previous steps based on results.\n"
+          ]
+        }
+      ],
       "source": [
         "res = zephyr.evaluate()"
       ]
@@ -675,10 +715,10 @@
               " 'sklearn.metrics.precision_score': 0.5,\n",
               " 'sklearn.metrics.f1_score': 0.6666666666666666,\n",
               " 'sklearn.metrics.recall_score': 1.0,\n",
-              " 'zephyr_ml.primitives.postprocessing.confusion_matrix': (array([[1, 1],\n",
+              " 'zephyr_ml.primitives.evaluation.confusion_matrix': (array([[1, 1],\n",
               "         [0, 1]]),\n",
               "  <Figure size 640x480 with 2 Axes>),\n",
-              " 'zephyr_ml.primitives.postprocessing.roc_auc_score_and_curve': (0.5,\n",
+              " 'zephyr_ml.primitives.evaluation.roc_auc_score_and_curve': (0.5,\n",
               "  <Figure size 640x480 with 1 Axes>)}"
             ]
           },
@@ -719,13 +759,13 @@
       ],
       "source": [
         "%matplotlib inline\n",
-        "_, conf_matrix_fig = res[\"zephyr_ml.primitives.postprocessing.confusion_matrix\"]\n",
+        "_, conf_matrix_fig = res[\"zephyr_ml.primitives.evaluation.confusion_matrix\"]\n",
         "conf_matrix_fig"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 8,
+      "execution_count": 9,
       "id": "d59e86b1",
       "metadata": {},
       "outputs": [
@@ -736,17 +776,25 @@
               "<Figure size 640x480 with 1 Axes>"
             ]
           },
-          "execution_count": 8,
+          "execution_count": 9,
           "metadata": {},
           "output_type": "execute_result"
         }
       ],
       "source": [
         "\n",
-        "_, roc_fig = res[\"zephyr_ml.primitives.postprocessing.roc_auc_score_and_curve\"]\n",
+        "_, roc_fig = res[\"zephyr_ml.primitives.evaluation.roc_auc_score_and_curve\"]\n",
         "\n",
         "roc_fig\n"
       ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "id": "38d109a1",
+      "metadata": {},
+      "outputs": [],
+      "source": []
     }
   ],
   "metadata": {