Update my_pages/rashomon_effect.py

my_pages/rashomon_effect.py

@@ -4,7 +4,17 @@ import numpy as np
 from utils import go_to
 
 def render():
-    st.title("Rashomon Effect")
+    st.markdown(
+        """
+        <div style='text-align: center; font-size:18px; color:gray;'>
+        Consider data about individuals who paid back their loans (green) and those who defaulted (red). <br>
+        Which model out of the two will you choose as your final model to give loan applications? <br><br>
+        </div>
+        """,
+        unsafe_allow_html=True
+    )
+
+    st.markdown("---")
 
     # Generate synthetic data
     np.random.seed(42)
@@ -21,7 +31,10 @@ def render():
         ax.scatter(x, y, c=colors, alpha=0.6)
         ax.set_xlabel("Annual Income")
         ax.set_ylabel("Credit Score")
-        ax.set_title(title)
+        # ax.set_title(title)
+
+        fig.patch.set_alpha(0)
+        ax.patch.set_alpha(0)
 
         # Decision boundary
         if decision_boundary is not None:
@@ -46,23 +59,25 @@ def render():
         return fig
 
     # Top scatter plot (centered to match smaller width)
-    col1, col2, col3, col4, col5 = st.columns([1, 1, 1, 1, 1])
-    with col3:
+    col1, col2, col3 = st.columns([1.5, 1, 1.5])
+    with col2:
         st.pyplot(plot_scatter(income, credit, colors, title="Original Data"))
 
+    col1, col2, col3, col4 = st.columns([1, 1, 1, 1])
     with col2:
         st.pyplot(plot_scatter(income, credit, colors, title="Vertical Boundary",
                                decision_boundary=55, boundary_type="vertical"))
         left_selected = st.button("Choose Vertical Boundary")
-    with col4:
+    with col3:
         st.pyplot(plot_scatter(income, credit, colors, title="Horizontal Boundary",
                                decision_boundary=55, boundary_type="horizontal"))
         right_selected = st.button("Choose Horizontal Boundary")
 
+    col1, col2, col3 = st.columns([1.5, 1, 1.5])
     # Show new individual based on selection
     if left_selected:
         new_point = (40, 80)  # High credit score, low income
-        with col3:
+        with col2:
             st.pyplot(plot_scatter(income, credit, colors,
                                    title="Vertical Boundary + New Individual",
                                    decision_boundary=55, boundary_type="vertical",
@@ -70,7 +85,7 @@ def render():
         st.warning("This individual was rejected by your chosen model. Why not choose a model that helps them?")
     elif right_selected:
         new_point = (80, 40)  # Low credit score, high income
-        with col3:
+        with col2:
             st.pyplot(plot_scatter(income, credit, colors,
                                    title="Horizontal Boundary + New Individual",
                                    decision_boundary=55, boundary_type="horizontal",