Hi,
I have deployed web app (learning analytic web) in streamlit share as follows:
App URL:
https://share.streamlit.io/59er/eng_learning_analytics_web/eng_edu_login_app.py
User Name: demo01
Password: demo01
On the menu “Pass/Fail Prediction” in this app, decision tree graph and SHAP summary_plot do not work.
I think dtreeviz, graphviz and shap libraries may be successfully installed in the streamlit server.
This app is working on the Ubuntu server in my home. And, I did not find any difference of coding between these two.
Do you have any idea on this problem?
Coding is as follows:
fig = plt.figure(figsize = (5,5))
explainer = shap.TreeExplainer(load_clf,X)
shap_values = explainer.shap_values(X)
st.subheader('Impact of explanatory variables (each item score) on\
the objective variable (final score): Class 0 has an impact for Fail, Class 1 for Pass)')
fig = shap.summary_plot(shap_values, X , plot_type = 'bar')
st.pyplot(fig)
from dtreeviz.trees import dtreeviz
import graphviz as graphviz
import streamlit.components.v1 as components
viz = dtreeviz(
model,
X_train,
y_train,
target_name = 'Fail/Pass',
feature_names = X_train.columns,
class_names = ['Fail','Pass'],
)
def st_dtree(plot, height = None):
dtree_html = f'<body>{viz.svg()}</body>'
components.html(dtree_html, height = height)
st_dtree(dtreeviz(model, X_train, y_train,
target_name = 'Pass/Fail', feature_names = X_train.columns,
class_names = ['Fail','Pass']),400)
Your advice on this would be appreciated.