sklearn: class + regression notebooks

Author: bartzbeielstein

notebooks/10_spot_hpt_sklearn_classification.ipynb

@@ -6310,7 +6310,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.10"
   },
   "vscode": {
    "interpreter": {

notebooks/14_spot_ray_hpt_torch_cifar10.ipynb

@@ -32,7 +32,7 @@
     {
      "data": {
       "text/plain": [
-       "'10-sklearn_p040025_10min_50init_2023-05-09_00-04-46'"
+       "'10-sklearn_maans03_10min_50init_2023-05-09_11-57-59'"
       ]
      },
      "execution_count": 2,
@@ -79,8 +79,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "spotPython                                0.0.63\n",
-      "spotRiver                                 0.0.92\n",
+      "spotPython                        0.0.63\n",
+      "spotRiver                         0.0.92\n",
       "Note: you may need to restart the kernel to use updated packages.\n"
      ]
     }
@@ -433,6 +433,17 @@
     "    2. `metric_sklearn` is used for the sklearn based evaluation."
    ]
   },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Important**:\n",
+    "\n",
+    "* `spotPython` performs minimization by default.\n",
+    "* If accuracy or roc/auc should be maximized, then the objective function has to be multiplied by -1. Therefore, `weights` is set to -1 in this case."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 15,
@@ -567,7 +578,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "spotPython tuning: [##--------] 23.07% \r"
+      "spotPython tuning: [----------] 3.18% \r"
      ]
     }
    ],
@@ -908,7 +919,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.10"
   },
   "vscode": {
    "interpreter": {