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Anupam202224
commited on
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55b7970
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Parent(s):
85f1529
Update app.py
Browse files
app.py
CHANGED
@@ -1,7 +1,13 @@
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import pickle
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import gradio as gr
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import numpy as np
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# Load the trained model
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model = pickle.load(open('/content/heart_disease_model.sav', 'rb'))
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@@ -9,7 +15,7 @@ model = pickle.load(open('/content/heart_disease_model.sav', 'rb'))
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def predict_heart_disease(age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal):
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input_data = np.array([[age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal]])
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prediction = model.predict(input_data)
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if prediction[0] == 1:
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return "The person has heart disease."
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else:
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@@ -43,3 +49,6 @@ def heart_disease_interface():
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# Launch the Gradio Interface
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heart_disease_interface().launch()
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.linear_model import LogisticRegression
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import pickle
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import gradio as gr
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import numpy as np
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# Load the CSV data
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data = pd.read_csv('/content/Untitled spreadsheet - Heart desiese data.csv') # Ensure the correct file path
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# Load the trained model
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model = pickle.load(open('/content/heart_disease_model.sav', 'rb'))
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def predict_heart_disease(age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal):
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input_data = np.array([[age, sex, cp, trestbps, chol, fbs, restecg, thalach, exang, oldpeak, slope, ca, thal]])
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prediction = model.predict(input_data)
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if prediction[0] == 1:
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return "The person has heart disease."
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else:
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# Launch the Gradio Interface
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heart_disease_interface().launch()
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# Check the first few rows of the data (optional)
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print(data.head())
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