File size: 554 Bytes
94f2e22 a7d3ccb 94f2e22 c9c9606 a7d3ccb 43f51cb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
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)
sWid = st.slider('Sepal width (cm.)', 0.0, 10.0)
pLen = st.slider('Petal lenght (cm.)', 0.0, 10.0)
pWid = st.slider('Pepal 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]) |