Update app.py

app.py

@@ -1,4 +1,5 @@
 import streamlit as st
+from sklearn import neighbors, datasets
 
 with st.form(key='my_form'):
   sLen = st.slider('Sepal lenght(cm) ', 0.0, 10.0)
@@ -6,3 +7,10 @@ with st.form(key='my_form'):
   pLen = st.slider('Petal lenght(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]])
+print(iris.target_names[knn.predict([[3,5,4,2]])])