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| import streamlit as st | |
| import numpy as np | |
| import pickle | |
| import streamlit.components.v1 as components | |
| # Load the pickled model | |
| def load_model(): | |
| return pickle.load(open('Employee_Attrition_ra.pkl', 'rb')) | |
| # Function for model prediction | |
| def model_prediction(model, features): | |
| predicted = str(model.predict(features)[0]) | |
| return predicted | |
| def app_design(): | |
| # Add input fields for High, Open, and Low values | |
| image = '13.png' | |
| st.image(image, use_column_width=True) | |
| st.subheader("Enter the following values:") | |
| Age = st.number_input("Age") | |
| BusinessTravel = st.number_input("Business Travel") | |
| DailyRate = st.number_input("Daily Rate") | |
| Department = st.number_input("Department") | |
| DistanceFromHome = st.number_input("Distance From Home") | |
| Education = st.number_input("Education") | |
| EducationField = st.number_input("Education Field") | |
| EmployeeCount = st.number_input("Employee Count") | |
| EmployeeNumber = st.number_input("Employee Number") | |
| EnvironmentSatisfaction = st.number_input("Environment Satisfaction") | |
| Gender = st.selectbox('Gender',('Male','Female')) | |
| if Gender == 'Male': | |
| Gender = 0 | |
| elif Gender == 'Female': | |
| Gender = 1 | |
| HourlyRate = st.number_input("Hourly Rate") | |
| JobInvolvement = st.number_input("Job Involvement") | |
| JobLevel = st.number_input("Job Level") | |
| JobRole = st.number_input("Job Role") | |
| JobSatisfaction = st.number_input("JobSatisfaction") | |
| MaritalStatus = st.number_input("Marital Status") | |
| MonthlyIncome = st.number_input("Monthly Income") | |
| MonthlyRate = st.number_input("Monthly Rate") | |
| NumCompaniesWorked = st.number_input("Number of Companies in you worked") | |
| Over18 = st.number_input("Over 18 age") | |
| OverTime = st.number_input("Overtime hours") | |
| PercentSalaryHike = st.number_input("Percent Salary Hike") | |
| PerformanceRating = st.number_input("Performance Rating") | |
| RelationshipSatisfaction = st.number_input("Relationship Satisfaction") | |
| StandardHours = st.number_input("Standard Hours") | |
| StockOptionLevel = st.number_input("Stock Option Level") | |
| TotalWorkingYears = st.number_input("Total Working Years") | |
| TrainingTimesLastYear = st.number_input("Training Times Last Year") | |
| WorkLifeBalance = st.number_input("Work Life Balance") | |
| YearsAtCompany = st.number_input("Years At Company") | |
| YearsInCurrentRole = st.number_input("Years In Current Role") | |
| YearsSinceLastPromotion = st.number_input("Years Since Last Promotion") | |
| YearsWithCurrManager = st.number_input("Years With Current Manager") | |
| # Create a feature list from the user inputs | |
| features = [[Age,BusinessTravel,DailyRate,Department,DistanceFromHome,Education,EducationField,EmployeeCount,EmployeeNumber,EnvironmentSatisfaction,Gender,HourlyRate,JobInvolvement,JobLevel,JobRole,JobSatisfaction,MaritalStatus,MonthlyIncome,MonthlyRate,NumCompaniesWorked,Over18,OverTime,PercentSalaryHike,PerformanceRating,RelationshipSatisfaction,StandardHours,StockOptionLevel,TotalWorkingYears,TrainingTimesLastYear,WorkLifeBalance,YearsAtCompany,YearsInCurrentRole,YearsSinceLastPromotion,YearsWithCurrManager]] | |
| # Load the model | |
| model = load_model() | |
| # Make a prediction when the user clicks the "Predict" button | |
| if st.button('Predict Attrition'): | |
| predicted_value = model_prediction(model, features) | |
| if predicted_value == 0: | |
| st.success(f"The Employee will leave the company") | |
| else: | |
| st.success(f"The Employee will not leave the company") | |
| def about_hidevs(): | |
| components.html(""" | |
| <div> | |
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| <a class="link" href="https://github.com/hidevscommunity" target="__blank">GitHub</a></p> | |
| </div> | |
| """, | |
| height=600) | |
| def main(): | |
| # Set the app title and add your website name and logo | |
| st.set_page_config( | |
| page_title="Employee Attrition Prediction", | |
| page_icon=":chart_with_upwards_trend:", | |
| ) | |
| st.title("Welcome to our Employee Attrition Prediction App!") | |
| app_design() | |
| st.header("About HiDevs Community") | |
| about_hidevs() | |
| if __name__ == '__main__': | |
| main() | |