app.py

import streamlit as st
from sklearn import neighbors, datasets

with st.form(key='my_form'):
  sLen = st.slider('sepal length (cm) ', 0.0, 10.0)
  sWid = st.slider('sepal width (cm) ', 0.0, 10.0)
  pLen = st.slider('petal length (cm) ', 0.0, 10.0)
  pWid = st.slider('petal width (cm) ', 0.0, 10.0)
  st.form_submit_button('Predict')

iris = datasets.load_iris()
X,y = iris.data, iris.target
knn = neighbors.KNeighborsClassifier(n_neighbors=2) #k = 3,4,5,6
knn.fit(X,y)
predict = knn.predict([[sLen,sWid,pLen,pWid]])
st.text(iris.target_names[predict])