update notebooks

Author: sborms

tutorials/tutorial_Cobra_linear_regression.ipynb

@@ -678,7 +678,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "49dad06c157f4f8090d641903bc5cfcb",
+       "model_id": "07f939a4565f4b639981a407ce99ffd2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -692,7 +692,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2e071e391a23452897628260b78ff01e",
+       "model_id": "f35c9b43811c4a01bad066dafe46b03a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -706,7 +706,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7c3142613dd84ed7aa9e0e87ab4e3631",
+       "model_id": "f6083ef6112e4cea81f4356926716dfb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -720,7 +720,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "0098bc6e4b474426b883e2dbf311c03a",
+       "model_id": "fbebd61d776341d3873e3a335e7d9b3d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -754,7 +754,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f6dd3c68d67d46b9b49594d0469bce95",
+       "model_id": "1d3f898080714ab39e25afd1d45567fe",
        "version_major": 2,
        "version_minor": 0
       },
@@ -768,7 +768,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "544e2955bcb149d68987fe54c6021e35",
+       "model_id": "4ff1db8f0ece413a8549163fde2cc809",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1997,7 +1997,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "2f0a1cf9b7d44a6aaae61e296659759a",
+       "model_id": "800c9244e7a0466c9a9e7dbf068a2720",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2058,7 +2058,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>[fare_enc, sex_enc, age_enc]</td>\n",
+       "      <td>[sex_enc, fare_enc, age_enc]</td>\n",
        "      <td>age_enc</td>\n",
        "      <td>0.841944</td>\n",
        "      <td>0.825715</td>\n",
@@ -2067,7 +2067,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>[fare_enc, age_enc, sex_enc, class_enc]</td>\n",
+       "      <td>[sex_enc, age_enc, fare_enc, class_enc]</td>\n",
        "      <td>class_enc</td>\n",
        "      <td>0.846151</td>\n",
        "      <td>0.837500</td>\n",
@@ -2076,7 +2076,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>[fare_enc, age_enc, class_enc, sex_enc, sibsp_...</td>\n",
+       "      <td>[sex_enc, age_enc, class_enc, fare_enc, sibsp_...</td>\n",
        "      <td>sibsp_enc</td>\n",
        "      <td>0.852089</td>\n",
        "      <td>0.844360</td>\n",
@@ -2085,7 +2085,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>[fare_enc, sibsp_enc, age_enc, class_enc, sex_...</td>\n",
+       "      <td>[class_enc, sibsp_enc, sex_enc, age_enc, fare_...</td>\n",
        "      <td>deck_enc</td>\n",
        "      <td>0.854462</td>\n",
        "      <td>0.844655</td>\n",
@@ -2094,7 +2094,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>6</th>\n",
-       "      <td>[fare_enc, sibsp_enc, age_enc, deck_enc, class...</td>\n",
+       "      <td>[class_enc, sibsp_enc, sex_enc, deck_enc, age_...</td>\n",
        "      <td>pclass_enc</td>\n",
        "      <td>0.854462</td>\n",
        "      <td>0.844655</td>\n",
@@ -2103,7 +2103,7 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>7</th>\n",
-       "      <td>[fare_enc, sibsp_enc, pclass_enc, age_enc, dec...</td>\n",
+       "      <td>[pclass_enc, class_enc, sibsp_enc, sex_enc, de...</td>\n",
        "      <td>parch_enc</td>\n",
        "      <td>0.856193</td>\n",
        "      <td>0.843981</td>\n",
@@ -2118,12 +2118,12 @@
        "                                          predictors last_added_predictor  \\\n",
        "0                                          [sex_enc]              sex_enc   \n",
        "1                                [sex_enc, fare_enc]             fare_enc   \n",
-       "2                       [fare_enc, sex_enc, age_enc]              age_enc   \n",
-       "3            [fare_enc, age_enc, sex_enc, class_enc]            class_enc   \n",
-       "4  [fare_enc, age_enc, class_enc, sex_enc, sibsp_...            sibsp_enc   \n",
-       "5  [fare_enc, sibsp_enc, age_enc, class_enc, sex_...             deck_enc   \n",
-       "6  [fare_enc, sibsp_enc, age_enc, deck_enc, class...           pclass_enc   \n",
-       "7  [fare_enc, sibsp_enc, pclass_enc, age_enc, dec...            parch_enc   \n",
+       "2                       [sex_enc, fare_enc, age_enc]              age_enc   \n",
+       "3            [sex_enc, age_enc, fare_enc, class_enc]            class_enc   \n",
+       "4  [sex_enc, age_enc, class_enc, fare_enc, sibsp_...            sibsp_enc   \n",
+       "5  [class_enc, sibsp_enc, sex_enc, age_enc, fare_...             deck_enc   \n",
+       "6  [class_enc, sibsp_enc, sex_enc, deck_enc, age_...           pclass_enc   \n",
+       "7  [pclass_enc, class_enc, sibsp_enc, sex_enc, de...            parch_enc   \n",
        "\n",
        "   train_performance  selection_performance  validation_performance  \\\n",
        "0           0.776059               0.744192                0.768315   \n",
@@ -2235,7 +2235,7 @@
     {
      "data": {
       "text/plain": [
-       "['fare_enc', 'age_enc', 'class_enc', 'sex_enc', 'sibsp_enc']"
+       "['sex_enc', 'age_enc', 'class_enc', 'fare_enc', 'sibsp_enc']"
       ]
      },
      "execution_count": 38,
@@ -2259,11 +2259,11 @@
     {
      "data": {
       "text/plain": [
-       "{'fare_enc': 0.7172923586385251,\n",
-       " 'age_enc': 3.643976017537654,\n",
-       " 'class_enc': 4.016803499515129,\n",
-       " 'sex_enc': 4.480325969907552,\n",
-       " 'sibsp_enc': 2.525112162892561}"
+       "{'sex_enc': 4.4803259699084785,\n",
+       " 'age_enc': 3.6439760175385074,\n",
+       " 'class_enc': 4.016803499515996,\n",
+       " 'fare_enc': 0.7172923586394532,\n",
+       " 'sibsp_enc': 2.5251121628934774}"
       ]
      },
      "execution_count": 39,
@@ -2321,7 +2321,7 @@
      "data": {
       "text/plain": [
        "{'meta': 'logistic-regression',\n",
-       " 'predictors': ['fare_enc', 'age_enc', 'class_enc', 'sex_enc', 'sibsp_enc'],\n",
+       " 'predictors': ['sex_enc', 'age_enc', 'class_enc', 'fare_enc', 'sibsp_enc'],\n",
        " '_eval_metrics_by_split': {'selection': 0.8443602693602693,\n",
        "  'train': 0.8520888109845166,\n",
        "  'validation': 0.8277080062794349},\n",
@@ -2341,12 +2341,12 @@
        "  'verbose': 0,\n",
        "  'warm_start': False},\n",
        " 'classes_': [0, 1],\n",
-       " 'coef_': [[0.7172923586385251,\n",
-       "   3.643976017537654,\n",
-       "   4.016803499515129,\n",
-       "   4.480325969907552,\n",
-       "   2.525112162892561]],\n",
-       " 'intercept_': [-6.594091554186414],\n",
+       " 'coef_': [[4.4803259699084785,\n",
+       "   3.6439760175385074,\n",
+       "   4.016803499515996,\n",
+       "   0.7172923586394532,\n",
+       "   2.5251121628934774]],\n",
+       " 'intercept_': [-6.594091554184244],\n",
        " 'n_iter_': [5]}"
       ]
      },
@@ -2434,7 +2434,7 @@
     {
      "data": {
       "text/plain": [
-       "0.387648431025595"
+       "0.3876484310265555"
       ]
      },
      "execution_count": 45,