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9acee42 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | import streamlit as st
import pandas as pd
import pickle
from PIL import Image
def run():
# load model
with open('model.pkl', 'rb') as model:
model = pickle.load(model)
age = st.number_input('Age', min_value=18, max_value=100)
job = st.selectbox('Job', options=['technician', 'management', 'retired', 'student', 'unemployed', 'admin', 'services', 'blue-collar', 'enterpreneur', 'housemaid', 'unknown', 'self-employed']),
marital = st.selectbox('Marital status', options=['married', 'divorced', 'single']),
education = st.selectbox('Education', options=['primary', 'tertiary', 'secondary', 'unknown']),
default = st.selectbox('Default status',options=['yes', 'no']),
balance = st.number_input('Balance', min_value=0.0, max_value=80000.0),
housing = st.selectbox('Has housing loans ?',options=['no', 'yes']),
loan = st.selectbox('Has personal loan ?',options=['no', 'yes']),
contact = st.selectbox('Contacted by',options=['unknown', 'cellular', 'cellular', 'telephone', 'cellular']),
day = st.number_input('Day',min_value=1, max_value=31),
month = st.selectbox('Month', options=['jan','feb','mar','apr','may','jun','jul','aug','sep','oct','nov','dec']),
duration = st.number_input('Call duration (sec)',min_value=2, max_value=3881),
campaign = st.number_input('How many campaign that have been conducted ?',min_value=1, max_value=63),
pdays = st.number_input('Number of days passed',min_value=0, max_value=854),
previous = st.number_input('Number of contacts performed before',min_value=0, max_value=58),
poutcome = st.selectbox('Previous result',options=['unknown', 'success','other', 'failure'])
st.markdown('**Berikut adalah data yang telah kamu input :**')
dataInf = pd.DataFrame({
'age' : age,
'job' : job,
'marital' : marital,
'education' : education,
'default' : default,
'balance' : balance,
'housing' : housing,
'loan' : loan,
'contact' : contact,
'day' : day,
'month' : month,
'duration' : duration,
'campaign' : campaign,
'pdays' : pdays,
'previous' : previous,
'poutcome' : poutcome
}, index=[0])
st.table(dataInf)
if st.button(label='Predict'):
# data dummy prediction
yPred_inf = model.predict(dataInf)
# result of prediction
if yPred_inf[0] == 0:
st.write('Bukan client potensial')
else:
st.write('Client potensial') |