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import gradio as gr
import pickle
filename = 'GBR-insurance-prediction.sav'
loaded_model = pickle.load(open(filename, 'rb'))
def age_group_selector(age_grp):
if age_grp == '18-24': return [1,0,0,0,0,0,0,0]
elif age_grp =='25-30':return [0,1,0,0,0,0,0,0]
elif age_grp =='31-36':return [0,0,1,0,0,0,0,0]
elif age_grp =='37-42':return [0,0,0,1,0,0,0,0]
elif age_grp =='43-48':return [0,0,0,0,1,0,0,0]
elif age_grp =='49-54':return [0,0,0,0,0,1,0,0]
elif age_grp =='54-60':return [0,0,0,0,0,0,1,0]
elif age_grp =='61-64':return [0,0,0,0,0,0,0,1]
elif age_grp =='64+:': return [0,0,0,0,0,0,0,1]
def bmi_selector(bmi):
if bmi == '0-18.4 (Underweight)':return [1,0,0,0,0]
elif bmi == '18.5-24.9 (Healthy Weight)':return [0,1,0,0,0]
elif bmi == '25.0-29.9 (Overweight)':return [0,0,1,0,0]
elif bmi == '30-39.0 (Obese)': return [0,0,0,1,0]
elif bmi == '40+ (Severely Obese)': return [0,0,0,0,1]
def predict_insurance(sex,smoker,children,age_grp,bmi):
to_predict = []
if sex == 'male':
to_predict.append(1)
else:
to_predict.append(0)
if smoker == 'yes':
to_predict.append(1)
else:
to_predict.append(0)
to_predict.append(children)
to_predict = to_predict + age_group_selector(age_grp)
to_predict = to_predict + bmi_selector(bmi)
return (loaded_model.predict([to_predict]))
# return to_predict
css = """
footer {display:none !important}
.output-markdown{display:none !important}
.gr-button-lg {
z-index: 14;
width: 113px;
height: 30px;
left: 0px;
top: 0px;
padding: 0px;
cursor: pointer !important;
background: none rgb(17, 20, 45) !important;
border: none !important;
text-align: center !important;
font-size: 14px !important;
font-weight: 500 !important;
color: rgb(255, 255, 255) !important;
line-height: 1 !important;
border-radius: 6px !important;
transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
box-shadow: none !important;
}
.gr-button-lg:hover{
z-index: 14;
width: 113px;
height: 30px;
left: 0px;
top: 0px;
padding: 0px;
cursor: pointer !important;
background: none rgb(66, 133, 244) !important;
border: none !important;
text-align: center !important;
font-size: 14px !important;
font-weight: 500 !important;
color: rgb(255, 255, 255) !important;
line-height: 1 !important;
border-radius: 6px !important;
transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;
box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;
}
"""
with gr.Blocks(title="Insurance Price Prediction | Data Science Dojo", css=css) as demo:
with gr.Row():
input_sex = gr.Radio(["male", "female"],label="Sex")
input_smoker = gr.Radio(["yes", "no"],label="Smoker")
with gr.Row():
input_children = gr.Slider(0, 5,label='Children',step=1)
with gr.Row():
input_age_group = gr.Dropdown(['18-24','25-30','31-36','37-42','43-48','49-54','54-60','61-64','64+'],label='Age Group')
with gr.Row():
input_bmi = gr.Dropdown(['0-18.4 (Underweight)','18.5-24.9 (Healthy Weight)','25.0-29.9 (Overweight)','30-39.0 (Obese)','40+ (Severely Obese)'],label='BMI Range')
with gr.Row():
insurance = gr.Textbox(label='Estimated Insurance')
btn_ins = gr.Button(value="Submit")
btn_ins.click(fn=predict_insurance, inputs=[input_sex,input_smoker,input_children,input_age_group,input_bmi], outputs=[insurance])
demo.launch() |