File size: 2,755 Bytes
d05b013 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | import joblib
import pandas as pd
from lifelines import CoxPHFitter
class HRAttritionModel:
def __init__(self, model_path):
self.model = joblib.load(model_path)
self.features = ['Age', 'DistanceFromHome', 'Education', 'NumCompaniesWorked', 'PercentSalaryHike',
'TotalWorkingYears', 'TrainingTimesLastYear', 'WorkLifeBalance', 'YearsInCurrentRole',
'YearsSinceLastPromotion', 'YearsWithCurrManager', 'BusinessTravel_Travel_Rarely',
'BusinessTravel_Travel_Frequently', 'Department_Research & Development', 'Department_Sales',
'EducationField_Life Sciences', 'EducationField_Medical', 'EducationField_Marketing',
'EducationField_Other', 'EducationField_Technical Degree', 'Gender_Male', 'JobRole_Research Scientist',
'JobRole_Sales Executive', 'JobRole_Laboratory Technician', 'JobRole_Manufacturing Director',
'JobRole_Healthcare Representative', 'JobRole_Manager', 'JobRole_Sales Representative',
'JobRole_Research Director', 'MaritalStatus_Married', 'MaritalStatus_Single', 'OverTime_Yes']
def predict_survival(self, input_data):
df = pd.DataFrame([input_data], columns=self.features)
survival_function = self.model.predict_survival_function(df)
return survival_function.T
# Load the model and make a prediction for testing
if __name__ == "__main__":
model = HRAttritionModel('cox_model.pkl')
sample_input = {'Age': 41, 'DistanceFromHome': 1, 'Education': 2, 'NumCompaniesWorked': 1, 'PercentSalaryHike': 11,
'TotalWorkingYears': 8, 'TrainingTimesLastYear': 0, 'WorkLifeBalance': 1, 'YearsInCurrentRole': 4,
'YearsSinceLastPromotion': 0, 'YearsWithCurrManager': 5, 'BusinessTravel_Travel_Rarely': 1,
'BusinessTravel_Travel_Frequently': 0, 'Department_Research & Development': 0, 'Department_Sales': 1,
'EducationField_Life Sciences': 1, 'EducationField_Medical': 0, 'EducationField_Marketing': 0,
'EducationField_Other': 0, 'EducationField_Technical Degree': 0, 'Gender_Male': 1,
'JobRole_Research Scientist': 0, 'JobRole_Sales Executive': 0, 'JobRole_Laboratory Technician': 0,
'JobRole_Manufacturing Director': 0, 'JobRole_Healthcare Representative': 0, 'JobRole_Manager': 0,
'JobRole_Sales Representative': 0, 'JobRole_Research Director': 0, 'MaritalStatus_Married': 0,
'MaritalStatus_Single': 1, 'OverTime_Yes': 0}
prediction = model.predict_survival(sample_input)
print(prediction)
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