datasciencedojo/Insurance-Price-Prediction

1import gradio as gr2import pickle3 4filename = 'GBR-insurance-prediction.sav'5loaded_model = pickle.load(open(filename, 'rb'))6 7 8def age_group_selector(age_grp):9  if age_grp == '18-24': return [1,0,0,0,0,0,0,0]10  elif age_grp =='25-30':return [0,1,0,0,0,0,0,0]11  elif age_grp =='31-36':return [0,0,1,0,0,0,0,0]12  elif age_grp =='37-42':return [0,0,0,1,0,0,0,0] 13  elif age_grp =='43-48':return [0,0,0,0,1,0,0,0]14  elif age_grp =='49-54':return [0,0,0,0,0,1,0,0]15  elif age_grp =='54-60':return [0,0,0,0,0,0,1,0]16  elif age_grp =='61-64':return [0,0,0,0,0,0,0,1]17  elif age_grp =='64+:': return [0,0,0,0,0,0,0,1]18  19def bmi_selector(bmi):20  if bmi == '0-18.4 (Underweight)':return [1,0,0,0,0]21  elif bmi == '18.5-24.9 (Healthy Weight)':return [0,1,0,0,0]22  elif bmi == '25.0-29.9 (Overweight)':return [0,0,1,0,0]23  elif bmi == '30-39.0 (Obese)': return [0,0,0,1,0]24  elif bmi == '40+ (Severely Obese)': return [0,0,0,0,1]25 26 27 28def predict_insurance(sex,smoker,children,age_grp,bmi):29    30    to_predict = []31    32    if sex == 'male':33      to_predict.append(1)34    else:35      to_predict.append(0)36 37    if smoker == 'yes':38      to_predict.append(1)39    else:40      to_predict.append(0)41 42    to_predict.append(children)43 44    to_predict = to_predict + age_group_selector(age_grp)45    46    to_predict = to_predict + bmi_selector(bmi)47    48    return (loaded_model.predict([to_predict]))49    # return to_predict50    51css = """52footer {display:none !important}53.output-markdown{display:none !important}54 55.gr-button-lg {56    z-index: 14;57    width: 113px;58    height: 30px;59    left: 0px;60    top: 0px;61    padding: 0px;62    cursor: pointer !important; 63    background: none rgb(17, 20, 45) !important;64    border: none !important;65    text-align: center !important;66    font-size: 14px !important;67    font-weight: 500 !important;68    color: rgb(255, 255, 255) !important;69    line-height: 1 !important;70    border-radius: 6px !important;71    transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;72    box-shadow: none !important;73}74.gr-button-lg:hover{75    z-index: 14;76    width: 113px;77    height: 30px;78    left: 0px;79    top: 0px;80    padding: 0px;81    cursor: pointer !important; 82    background: none rgb(66, 133, 244) !important;83    border: none !important;84    text-align: center !important;85    font-size: 14px !important;86    font-weight: 500 !important;87    color: rgb(255, 255, 255) !important;88    line-height: 1 !important;89    border-radius: 6px !important;90    transition: box-shadow 200ms ease 0s, background 200ms ease 0s !important;91    box-shadow: rgb(0 0 0 / 23%) 0px 1px 7px 0px !important;92}93"""94with gr.Blocks(title="Insurance Price Prediction | Data Science Dojo", css=css) as demo:95    with gr.Row():96        input_sex = gr.Radio(["male", "female"],label="Sex")97        input_smoker = gr.Radio(["yes", "no"],label="Smoker")98    with gr.Row():    99        input_children = gr.Slider(0, 5,label='Children',step=1)100    with gr.Row():101        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')102    with gr.Row():103        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')104    with gr.Row():105        insurance = gr.Textbox(label='Estimated Insurance')106    btn_ins = gr.Button(value="Submit")107    btn_ins.click(fn=predict_insurance, inputs=[input_sex,input_smoker,input_children,input_age_group,input_bmi], outputs=[insurance])108 109 110demo.launch()