BaseHole- overridable functions

book/chapters/model_training.ipynb

@@ -156,74 +156,13 @@
    "id": "c68cb61a",
    "metadata": {},
    "source": [
-    "**Evaluate**: The evaluate function, designed to be overridden, is where the performance metrics of the model are calculated and analyzed. This function is crucial for understanding the model's strengths and weaknesses."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "6bd158b8",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def evaluate(self):\n",
-    "    '''\n",
-    "    Evaluates the performance of the machine learning model.\n",
+    "Below are the further functions in this class which are being overridden in other classes:\n",
     "\n",
-    "    Returns:\n",
-    "        None\n",
-    "    '''\n",
-    "    pass"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "92ea746f",
-   "metadata": {},
-   "source": [
-    "**Get Model**: The get_model function, another overridable method, is responsible for returning the specific machine learning model object that will be used for training and prediction."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "70730bfb",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_model(self):\n",
-    "    '''\n",
-    "    Get the machine learning model.\n",
+    "   - **Evaluate**: The evaluate function, designed to be overridden, is where the performance metrics of the model are calculated and analyzed. This function is crucial for understanding the model's strengths and weaknesses.\n",
     "\n",
-    "    Returns:\n",
-    "        object: The machine learning model.\n",
-    "    '''\n",
-    "    pass"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6535a559",
-   "metadata": {},
-   "source": [
-    "**Post-processing**: The post_processing function handles the final steps after model predictions are made, such as generating visualizations, analyzing feature importance, and saving results."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "9ffc7947",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def post_processing(self):\n",
-    "    '''\n",
-    "    Perform post-processing on the model's predictions.\n",
+    "   - **Get Model**: The get_model function, another overridable method, is responsible for returning the specific machine learning model object that will be used for training and prediction.\n",
     "\n",
-    "    Returns:\n",
-    "        None\n",
-    "    '''\n",
-    "    pass"
+    "   - **Post-processing**: The post_processing function handles the final steps after model predictions are made, such as generating visualizations, analyzing feature importance, and saving results."
    ]
   },
   {