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| import gradio as gr | |
| import pandas as pd | |
| import joblib | |
| age_input = gr.Number(label="Age") | |
| duration_input = gr.Number(label='Duration(Sec)') | |
| cc_contact_freq_input = gr.Number(label='CC Contact Freq') | |
| days_since_pc_input = gr.Number(label='Days Since PC') | |
| pc_contact_freq_input = gr.Number(label='Pc Contact Freq') | |
| job_input = gr.Dropdown(['admin.', 'blue-collar', 'technician', 'services', 'management', | |
| 'retired', 'entrepreneur', 'self-employed', 'housemaid', 'unemployed', | |
| 'student', 'unknown'],label="Job") | |
| marital_input = gr.Dropdown(['married', 'single', 'divorced', 'unknown'],label='Marital Status') | |
| education_input = gr.Dropdown(['experience', 'university degree', 'high school', 'professional.course', | |
| 'Others', 'illiterate'],label='Education') | |
| defaulter_input = gr.Dropdown(['no', 'unknown', 'yes'],label='Defaulter') | |
| home_loan_input = gr.Dropdown(['yes', 'no', 'unknown'],label='Home Loan') | |
| personal_loan_input = gr.Dropdown(['yes', 'no', 'unknown'],label='Personal Loan') | |
| communication_type_input = gr.Dropdown(['cellular', 'telephone'],label='Communication Type') | |
| last_contacted_input = gr.Dropdown(['may', 'jul', 'aug', 'jun', 'nov', 'apr', 'oct', 'mar', 'sep', 'dec'],label='Last Contacted') | |
| day_of_week_input = gr.Dropdown(['thu', 'mon', 'wed', 'tue', 'fri'],label='Day of Week') | |
| pc_outcome_input = gr.Dropdown(['nonexistent', 'failure', 'success'], label='PC Outcome') | |
| o = gr.Textbox() | |
| # load the model | |
| model = joblib.load('model.joblib') | |
| i2l = ['Not subscribed', 'Subscribed'] | |
| def fn(age, duration, cc_contact_freq, days_since_pc, pc_contact_freq, job, marital_status, education, | |
| defaulter, home_loan, personal_loan, communication_type, last_contacted, | |
| day_of_week, pc_outcome): | |
| sample = { | |
| 'Age': age, | |
| 'Duration(Sec)': duration, | |
| 'CC Contact Freq': cc_contact_freq, | |
| 'Days Since PC': days_since_pc, | |
| 'PC Contact Freq': pc_contact_freq, | |
| 'Job': job, | |
| 'Marital Status': marital_status, | |
| 'Education': education, | |
| 'Defaulter': defaulter, | |
| 'Home Loan': home_loan, | |
| 'Personal Loan': personal_loan, | |
| 'Communication Type': communication_type, | |
| 'Last Contacted': last_contacted, | |
| 'Day of Week': day_of_week, | |
| 'PC Outcome': pc_outcome, | |
| } | |
| print(f'sample: {sample}') | |
| data_point = pd.DataFrame([sample]) | |
| print(f'{data_point}') | |
| result = model.predict(data_point) | |
| result = result[0] | |
| print(result) | |
| return i2l[result] | |
| interface = gr.Interface(fn, | |
| inputs = [age_input, | |
| duration_input, | |
| cc_contact_freq_input, | |
| days_since_pc_input, | |
| pc_contact_freq_input, | |
| job_input, | |
| marital_input, | |
| education_input, | |
| defaulter_input, | |
| home_loan_input, | |
| personal_loan_input, | |
| communication_type_input, | |
| last_contacted_input, | |
| day_of_week_input, | |
| pc_outcome_input], | |
| outputs = o) | |
| interface.launch(share=True) |