import streamlit as st
import pickle
import sklearn
import joblib
import pandas as pd

joblib_file = "modelIris.pkl"
model = joblib.load(joblib_file)

sepal_length = st.text_input("sepal_length :", "")
sepal_width = st.text_input("sepal_width :", "")
petal_length = st.text_input("petal_length :", "")
petal_width = st.text_input("petal_width :", "")

if (sepal_length and sepal_width and petal_length and petal_width) :
    irisX = pd.DataFrame({
    'sepal_length': [float(sepal_length)],
    'sepal_width': [float(sepal_width)],
    'petal_length': [float(petal_length)],
    'petal_width': [float(petal_width)]
    })
    Y_pred = model.predict_proba(irisX)[0]
    
    if Y_pred[0] > Y_pred[1] and Y_pred[0]> Y_pred[2]:
        st.text("setosa")
    elif Y_pred[1] > Y_pred[0] and Y_pred[1]> Y_pred[2] :
        st.text("versicolor")
    else :
        st.text("virginica")
    
    
else :
    st.text("Remplis tous les champs")
69760c3ab6120b988a12b43b74467df68e0e674a
<mask token>

<mask token>
if sepal_length and sepal_width and petal_length and petal_width:
    irisX = pd.DataFrame({'sepal_length': [float(sepal_length)],
        'sepal_width': [float(sepal_width)], 'petal_length': [float(
        petal_length)], 'petal_width': [float(petal_width)]})
    Y_pred = model.predict_proba(irisX)[0]
    if Y_pred[0] > Y_pred[1] and Y_pred[0] > Y_pred[2]:
        st.text('setosa')
    elif Y_pred[1] > Y_pred[0] and Y_pred[1] > Y_pred[2]:
        st.text('versicolor')
    else:
        st.text('virginica')
else:
    st.text('Remplis tous les champs')

<mask token>
joblib_file = 'modelIris.pkl'
model = joblib.load(joblib_file)
sepal_length = st.text_input('sepal_length :', '')
sepal_width = st.text_input('sepal_width :', '')
petal_length = st.text_input('petal_length :', '')
petal_width = st.text_input('petal_width :', '')
if sepal_length and sepal_width and petal_length and petal_width:
    irisX = pd.DataFrame({'sepal_length': [float(sepal_length)],
        'sepal_width': [float(sepal_width)], 'petal_length': [float(
        petal_length)], 'petal_width': [float(petal_width)]})
    Y_pred = model.predict_proba(irisX)[0]
    if Y_pred[0] > Y_pred[1] and Y_pred[0] > Y_pred[2]:
        st.text('setosa')
    elif Y_pred[1] > Y_pred[0] and Y_pred[1] > Y_pred[2]:
        st.text('versicolor')
    else:
        st.text('virginica')
else:
    st.text('Remplis tous les champs')

import streamlit as st
import pickle
import sklearn
import joblib
import pandas as pd
joblib_file = 'modelIris.pkl'
model = joblib.load(joblib_file)
sepal_length = st.text_input('sepal_length :', '')
sepal_width = st.text_input('sepal_width :', '')
petal_length = st.text_input('petal_length :', '')
petal_width = st.text_input('petal_width :', '')
if sepal_length and sepal_width and petal_length and petal_width:
    irisX = pd.DataFrame({'sepal_length': [float(sepal_length)],
        'sepal_width': [float(sepal_width)], 'petal_length': [float(
        petal_length)], 'petal_width': [float(petal_width)]})
    Y_pred = model.predict_proba(irisX)[0]
    if Y_pred[0] > Y_pred[1] and Y_pred[0] > Y_pred[2]:
        st.text('setosa')
    elif Y_pred[1] > Y_pred[0] and Y_pred[1] > Y_pred[2]:
        st.text('versicolor')
    else:
        st.text('virginica')
else:
    st.text('Remplis tous les champs')

import streamlit as st
import pickle
import sklearn
import joblib
import pandas as pd

joblib_file = "modelIris.pkl"
model = joblib.load(joblib_file)

sepal_length = st.text_input("sepal_length :", "")
sepal_width = st.text_input("sepal_width :", "")
petal_length = st.text_input("petal_length :", "")
petal_width = st.text_input("petal_width :", "")

if (sepal_length and sepal_width and petal_length and petal_width) :
    irisX = pd.DataFrame({
    'sepal_length': [float(sepal_length)],
    'sepal_width': [float(sepal_width)],
    'petal_length': [float(petal_length)],
    'petal_width': [float(petal_width)]
    })
    Y_pred = model.predict_proba(irisX)[0]
    
    if Y_pred[0] > Y_pred[1] and Y_pred[0]> Y_pred[2]:
        st.text("setosa")
    elif Y_pred[1] > Y_pred[0] and Y_pred[1]> Y_pred[2] :
        st.text("versicolor")
    else :
        st.text("virginica")
    
    
else :
    st.text("Remplis tous les champs")