added a conclusion to each notebook, and cleaned up notebook

Author: DerikVo

Created_images/Neural Network confusion matrix.png

@@ -642,7 +642,9 @@
    "id": "d267e36b-9eb2-4301-b186-c09e4ce65af0",
    "metadata": {},
    "source": [
-    "Overall, our classes are balanced between the classes 'glioma', 'meningioma', 'notumor', and 'pituitary' in both our training and testing datasets. Additionally when looking at the average pixel value and the contrast between those average we can see some distinct features within those classes. This indicates that there are features that our model can learn to distinguish images into classes."
+    "Overall, our classes are balanced between the classes 'glioma', 'meningioma', 'notumor', and 'pituitary' in both our training and testing datasets. Additionally when looking at the average pixel value and the contrast between those average we can see some distinct features within those classes. This indicates that there are features that our model can learn to distinguish images into classes.\n",
+    "\n",
+    "We will know move onto building [A baseine model](../Notebooks/02_Baseline Model.ipynb)"
    ]
   }
  ],

Notebooks/01_EDA.ipynb

@@ -149,6 +149,20 @@
    "source": [
     "metrics_df.to_csv('../NoteBooks/scores.csv', index_label='Model')"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "94ad2e3d-8e0f-4fac-af2c-5a4b08ce540c",
+   "metadata": {},
+   "source": [
+    "_______________________________________________________________________________________________________________________-\n",
+    "# Conclusion:\n",
+    "\n",
+    "\n",
+    "Our baseline model has an accuracy of 46% which is better than simply guessing one class. This model simply compares which class an image belongs to by seeing the avg pixel value of a class and the image and seeing which class the image is closest to. \n",
+    "\n",
+    "We will now move into a more complex mode, a [neural network](../Notebooks/03_Neural_network.ipynb), to classify our images."
+   ]
   }
  ],
  "metadata": {