Upload app.py

app.py

@@ -176,7 +176,15 @@ def y1_interpret_xgb(*args):
     df = pd.DataFrame([args], columns=x1.columns)
     df = df.astype({col: "category" for col in categorical_columns1})
     shap_values = y1_explainer_xgb.shap_values(xgb.DMatrix(df, enable_categorical=True))
-    return shap.bar_plot(shap_values[0], max_display=15, show=False)
+    fig_m = shap.bar_plot(shap_values[0], max_display = 10, show = False)
+    fig_m = plt.gcf()
+    ax_m = plt.gca()
+    fig_m.set_figheight(6)
+    fig_m.set_figwidth(6)
+    plt.xlabel("SHAP value (impact on model output)", fontsize =12, fontweight = 'heavy', labelpad = 8)
+    plt.tick_params(axis="y",direction="out", labelsize = 12)
+    plt.tick_params(axis="x",direction="out", labelsize = 12)
+    return fig_m
 
 def y1_interpret_lgb(*args):
     df = pd.DataFrame([args], columns=x1_lgb.columns)