Update predictor.py

predictor.py

@@ -4,6 +4,7 @@ import numpy as np
 import lightgbm as lgb
 from lightgbm.callback import early_stopping
 import shap
+import streamlit as st
 
 from sklearn.ensemble import GradientBoostingRegressor
 from sklearn.model_selection import train_test_split
@@ -119,14 +120,16 @@ def create_shap_models(data):
     obj1 = shap.force_plot(explainer.expected_value, shap_values=shap_values, feature_names=data.columns)
     
     shap.initjs()
-    obj2 = shap.decision_plot(explainer.expected_value, shap_values, feature_names=np.array(data.columns))
+    shap.decision_plot(explainer.expected_value, shap_values, feature_names=np.array(data.columns))
+    st.pyplot(bbox_inches='tight')
     
     shap.initjs()
-    obj3 = shap.summary_plot(shap_values=shap_values, feature_names=data.columns)
+    shap.summary_plot(shap_values=shap_values, feature_names=data.columns)
+    st.pyplot(bbox_inches='tight')
     
     interaction_values = explainer.shap_interaction_values(data)
     interaction_values[0].round(2)
-    pd.DataFrame(interaction_values[0].round(2)).head(60)
+    st.write(pd.DataFrame(interaction_values[0].round(2)).head(60))
 
-    objs = [obj1,obj2,obj3]
-    return objs
+    
+    return obj1