Hemg commited on
Commit
e4a7bb2
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1 Parent(s): e9df9b2

Update app.py

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Files changed (1) hide show
  1. app.py +3 -3
app.py CHANGED
@@ -1,4 +1,4 @@
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- import gradio as gr
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  import joblib
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  import numpy as np
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  import pandas as pd
@@ -33,10 +33,10 @@ def encode_categorical_columns(df):
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  def predict_performance(Location, Course, College, Faculty, Source, Event, Presenter, Visited_Parent, Visited_College_for_Inquiry, Attended_Any_Event, College_Fee, GPA, Year):
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  input_data = [Location, Course, College, Faculty, Source, Event, Presenter, Visited_Parent, Visited_College_for_Inquiry, Attended_Any_Event, College_Fee, GPA, Year]
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- # Updated feature names to use underscores instead of spaces
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  feature_names = [
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  "Location", "Course", "College", "Faculty", "Source", "Event", "Presenter",
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- "Visited_Parent", "Visited_College_for_Inquiry", "Attended_Any_Event", "College_Fee", "GPA", "Year"
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  ]
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  input_df = pd.DataFrame([input_data], columns=feature_names)
 
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+ mport gradio as gr
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  import joblib
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  import numpy as np
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  import pandas as pd
 
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  def predict_performance(Location, Course, College, Faculty, Source, Event, Presenter, Visited_Parent, Visited_College_for_Inquiry, Attended_Any_Event, College_Fee, GPA, Year):
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  input_data = [Location, Course, College, Faculty, Source, Event, Presenter, Visited_Parent, Visited_College_for_Inquiry, Attended_Any_Event, College_Fee, GPA, Year]
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+ # Updated feature names to use spaces instead of underscores to match training data
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  feature_names = [
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  "Location", "Course", "College", "Faculty", "Source", "Event", "Presenter",
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+ "Visited Parent", "Visited College for Inquiry", "Attended Any Event", "College Fee", "GPA", "Year"
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  ]
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  input_df = pd.DataFrame([input_data], columns=feature_names)