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import streamlit as st
import pandas as pd
import numpy as np
import pickle
import json
# Load data yang sudah dibuat di model
with open('pipe.pkl', 'rb') as file1:
pipe = pickle.load(file1)
with open('random_best.pkl', 'rb') as file2:
km = pickle.load(file2)
def run():
# Membuat form
with st.form(key='credit card default payment next month'):
id = st.number_input('Serial ID', 0, 1000000, 100, help='id dalam bentuk angka')
Flight = st.number_input('Flight', min_value=202, max_value=10000, value=2000, step=1, help='input nomor penerbangan')
Airline = st.selectbox('Maskapai', ('CO', 'US','AA', 'AS', 'DL', 'B6', 'HA', 'OO', '9E', 'OH', 'EV', 'XE', 'YV', 'UA', 'MQ', 'FL', 'F9', 'WN' ), help='maskaapinya keterangannya ada di google')
AirportFrom = st.selectbox('Airport From ', ('SFO', 'PHX', 'LAX', 'ANC', 'LAS', 'SLC', 'DEN', 'ONT'), help='nama bandara untuk keterangan lebih lanjut silahkan lihat di google')
AirportTo = st.selectbox('Airport To ', ('SFO', 'PHX', 'LAX', 'ANC', 'LAS', 'SLC', 'DEN', 'ONT'), help='nama bandara untuk keterangan lebih lanjut silahkan lihat di google')
DayOfWeek = st.selectbox('Hari ', (1, 2, 3, 4, 5, 6, 7), help='input daalam bentuk hari 1=senin , 2= selasa, 3= rabu, 4= kamis, 5= jumat, 6= Sabtu, 7= minggu')
Time = st.number_input('waktu', min_value=15, max_value=1000, value=999, step=1, help='input lama waktu penerbangan')
Length = st.number_input('jarak penerbangan', min_value=205, max_value=9999, value=2000, step=1, help='input jarak penerbangan')
submitted = st.form_submit_button('Predict')
st.write("---")
#buat dataframe yang telah dimasukkan
data_inf = {
'id': id,
'Airline': Flight,
'Flight': Airline,
'AirportFrom': AirportFrom,
'AirportTo': AirportTo,
'DayOfWeek': DayOfWeek,
'Time': Time,
'Length': Length,
}
data_inf = pd.DataFrame([data_inf])
st.dataframe(data_inf)
if submitted:
# Predict probabilities for the test set
probabilities = pipe.predict_proba(data_inf)
max_prob_indexes = np.argmax(probabilities, axis=1)
max_probabilities = probabilities[np.arange(len(probabilities)), max_prob_indexes]
prediksi = pipe.predict(data_inf)
# Ganti nilai-nilai di dalam array
prediksi_asli = np.where(prediksi == 1, 'delay', 'tidak delay')
print(probabilities)
st.write(f'prediksi 0 sebesar {probabilities[:, 0]} dan prediksi 1 sebesar {probabilities[:,1]} jadi diprediksi sebagai {prediksi_asli}')
if __name__ == '__main__':
run() |