VaAishvarR commited on
Commit
1854f5d
·
1 Parent(s): c2f5c14

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -7
app.py CHANGED
@@ -13,9 +13,9 @@ loaded_model = pickle.load(open("XGB_CLF_5Feature.pkl", 'rb'))
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  explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
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  # Create the main function for server
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- def main_func(Management,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,JobSatisfaction):
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- new_row = pd.DataFrame.from_dict({'Management':Management,'EmployeeWellBeing':EmployeeWellBeing,
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- 'EngagedAtWork':EngagedAtWork,'WorkEnvironment':WorkEnvironment,'JobSatisfaction':JobSatisfaction,
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  }, orient = 'index').transpose()
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  prob = loaded_model.predict_proba(new_row)
@@ -50,11 +50,11 @@ with gr.Blocks(title=title) as demo:
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  gr.Markdown("""---""")
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  with gr.Row():
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  with gr.Column():
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- Management = gr.Slider(label="Management Score", minimum=1, maximum=5, value=4, step=.1)
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  EmployeeWellBeing = gr.Slider(label="Employee Well Being Score", minimum=1, maximum=5, value=4, step=.1)
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  EngagedAtWork = gr.Slider(label="Work Engagement Score", minimum=1, maximum=5, value=4, step=.1)
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  WorkEnvironment = gr.Slider(label="Work Environment Score", minimum=1, maximum=5, value=4, step=.1)
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- JobSatisfaction = gr.Slider(label="Job Satisfaction Score", minimum=1, maximum=5, value=4, step=.1)
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  submit_btn = gr.Button("Analyze")
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  with gr.Column(visible=True) as output_col:
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  label = gr.Label(label = "Predicted Label")
@@ -62,13 +62,13 @@ with gr.Blocks(title=title) as demo:
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  submit_btn.click(
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  main_func,
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- [Management,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,JobSatisfaction],
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  [label,local_plot], api_name="Employee_Turnover"
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  )
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  gr.Markdown("### Click on any of the examples below to see how it works:")
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  gr.Examples([[4,4,4,4,5,5], [5,4,5,4,4,4]],
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- [Management,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,JobSatisfaction],
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  [label,local_plot], main_func, cache_examples=True)
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  demo.launch()
 
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  explainer = shap.Explainer(loaded_model) # PLEASE DO NOT CHANGE THIS.
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  # Create the main function for server
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+ def main_func(JobSatisfaction,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,Management):
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+ new_row = pd.DataFrame.from_dict({'JobSatisfaction':JobSatisfaction,'EmployeeWellBeing':EmployeeWellBeing,
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+ 'EngagedAtWork':EngagedAtWork,'WorkEnvironment':WorkEnvironment,'Management':Management,
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  }, orient = 'index').transpose()
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  prob = loaded_model.predict_proba(new_row)
 
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  gr.Markdown("""---""")
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  with gr.Row():
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  with gr.Column():
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+ JobSatisfaction = gr.Slider(label="Job Satisfaction Score", minimum=1, maximum=5, value=4, step=.1)
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  EmployeeWellBeing = gr.Slider(label="Employee Well Being Score", minimum=1, maximum=5, value=4, step=.1)
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  EngagedAtWork = gr.Slider(label="Work Engagement Score", minimum=1, maximum=5, value=4, step=.1)
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  WorkEnvironment = gr.Slider(label="Work Environment Score", minimum=1, maximum=5, value=4, step=.1)
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+ Management = gr.Slider(label="Management Score", minimum=1, maximum=5, value=4, step=.1)
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  submit_btn = gr.Button("Analyze")
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  with gr.Column(visible=True) as output_col:
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  label = gr.Label(label = "Predicted Label")
 
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  submit_btn.click(
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  main_func,
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+ [JobSatisfaction,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,Management],
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  [label,local_plot], api_name="Employee_Turnover"
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  )
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  gr.Markdown("### Click on any of the examples below to see how it works:")
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  gr.Examples([[4,4,4,4,5,5], [5,4,5,4,4,4]],
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+ [JobSatisfaction,EmployeeWellBeing,EngagedAtWork,WorkEnvironment,Management],
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  [label,local_plot], main_func, cache_examples=True)
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  demo.launch()