Update app.py

app.py

@@ -1,8 +1,17 @@
 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=6)
+knn.fit(x,y)
+predict = knn.predict([[sLen,sWid,pLen,pWid]])
+st.write(iris.target_names[predict([[3,5,4,2]])])