Update app.py

app.py

@@ -1,8 +1,16 @@
 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')
+  st.form_submit_button('predict')
+  
+  iris = datasets. load_iris()
+X, y = iris.data, iris.target
+knn = neighbors.KNeighborsClassifier(n_neighbors=3)
+knn.fit(X, y)
+predict = knn.predict([[sLen,swid,pLen,pWid]])
+st.write(iris.target_names[predict])