kingabzpro commited on
Commit
14b29ac
1 Parent(s): 6666b9d

Sync App files

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Files changed (1) hide show
  1. drug_app.py +22 -7
drug_app.py CHANGED
@@ -5,8 +5,22 @@ pipe = sio.load("./Model/drug_pipeline.skops", trusted=True)
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  def classifier(Age, Sex, BP, Cholesterol, Na_to_K):
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- pred_glass = pipe.predict([[Age, Sex, BP, Cholesterol, Na_to_K]])[0]
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- label = f"Predicted Glass label: **{pred_glass}**"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  return label
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@@ -19,11 +33,12 @@ inputs = [
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  ]
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  outputs = [gr.Label(num_top_classes=5)]
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- examples=[
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- [30, "M", "HIGH", "NORMAL", 15.4],
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- [35, "F", "LOW", "NORMAL", 8],
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- [50, "M", "HIGH", "HIGH", 34],
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- ]
 
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  title = "Drug Classification"
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  description = "Enter the details to correctly identify Drug type?"
 
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  def classifier(Age, Sex, BP, Cholesterol, Na_to_K):
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+ """
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+ This function takes input features Age, Sex, BP, Cholesterol, and Na_to_K,
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+ and uses a sklearn pipeline to make a prediction on the glass label.
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+
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+ Args:
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+ Age (float): The age of the patient
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+ Sex (str): The sex of the patient (M or F)
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+ BP (str): The blood pressure of the patient (HIGH, NORMAL, or LOW)
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+ Cholesterol (str): The cholesterol level of the patient (HIGH or NORMAL)
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+ Na_to_K (float): The ratio of sodium to potassium in the patient's blood
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+
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+ Returns:
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+ str: A string with the predicted drug label
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+ """
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+ pred_drug = pipe.predict([[Age, Sex, BP, Cholesterol, Na_to_K]])[0]
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+ label = f"Predicted Drug label: **{pred_drug}**"
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  return label
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  ]
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  outputs = [gr.Label(num_top_classes=5)]
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+ examples = [
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+ [30, "M", "HIGH", "NORMAL", 15.4],
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+ [35, "F", "LOW", "NORMAL", 8],
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+ [50, "M", "HIGH", "HIGH", 34],
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+ ]
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+
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  title = "Drug Classification"
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  description = "Enter the details to correctly identify Drug type?"