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app.py
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app.py
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from flask import *
app = Flask(__name__)
@app.route('/',methods =['POST','GET'])
def predict():
if request.method == 'POST':
import pandas
data = pandas.read_csv('data/pima.csv')
matrix = data.values
X = matrix[:,0:8]
Y = matrix[:,8]
from sklearn import model_selection
X_train,X_test,Y_train,Y_test = model_selection.train_test_split(X,Y,test_size = 0.3,random_state = 42)
from sklearn.ensemble import GradientBoostingClassifier, RandomForestClassifier
model = GradientBoostingClassifier()
model.fit(X_train,Y_train)
children = request.form['children']
glucose = request.form['glucose']
bp = request.form['bp']
st = request.form['st']
insulin = request.form['insulin']
bmi = request.form['bmi']
dpf = request.form['dpf']
age = request.form['age']
symptoms = [[
children,glucose,bp,st,insulin,bmi,dpf,age
]]
condition = model.predict(symptoms)
return render_template('predict.html',outcome = str(condition[0]))
return render_template('predict.html',message = 'The form was filled successfully')
app.run(debug=True)