Update app.py

app.py

@@ -52,4 +52,10 @@ hide_streamlit_style = """
             subheader {alignment: center;}
             </style>
             """
-st.markdown(hide_streamlit_style, unsafe_allow_html=True) 
+st.markdown(hide_streamlit_style, unsafe_allow_html=True) 
+
+st.markdown("""
+            There are several points to note on the effect of K on the quality of model fit:
+            * Models with extremely small values of K learn the local patterns and do not generalize well thus they have a high variance or overfitting effect.
+            * Models with extremely high values of K suffer from averaging effect over the entire space and thus do not do well even on the train points. This is known as a high bias or underfitting effect.
+            """)