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import skops.io as sio
import gradio as gr
#pipe = sio.load("bank_marketing_pipe.skops", trusted=True)
pipe = sio.load("sgd_bank_marketing_pipe.skops", trusted=True)
classes = [
"Not Subscribe",
"Subscribe"]
def classifier(age, job, marital, education, default, balance, housing,loan, contact):
pred = pipe.predict([[age, job, marital, education, default, balance, housing,loan, contact]])[0]
label = f"Predicted output: **{classes[pred]}**"
return label
inputs = [
gr.Slider(10, 90, step=1, label="Age"),
gr.Dropdown(["admin.","unknown","unemployed","management","housemaid","entrepreneur","student","blue-collar",
"self-employed","retired","technician","services"], label="Job", multiselect=False),
gr.Dropdown(["married","divorced","single"], label="Marital", multiselect=False),
gr.Dropdown(["unknown","secondary","primary","tertiary"], label="Education", multiselect=False),
gr.Radio(["yes","no"], label="Default", info='has credit in default?'),
gr.Slider(-100000, 100000, step=1, label="Balance"),
gr.Radio(["yes","no"], label="Housing", info='has housing loan?'),
gr.Radio(["yes","no"], label="Loan", info='has personal loan?'),
gr.Dropdown(["unknown","telephone","cellular"], label="Contact")
]
outputs = [gr.Label(num_top_classes=2)]
title = "Deposit Subscription Prediction"
description = "Enter the details to identify where or not the customer is subscribed or not subscribed for deposit"
gr.Interface(
fn=classifier,
inputs=inputs,
outputs=outputs,
title=title,
description=description,
).launch() |