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Apriori Algorithm, BackPropagationNeuralNetwork, Genetic Algorithm, K Medoid Algorithm, LogisticRegression, matrix multiplication, MultivariateRegression, PSO Particle Swarm Optimization, Principal Component Analysis, RSA ALGO, SparseMatrixMultiplication, SqrtFunction, Steepest Descent Search, Gradient Descent TSP, abc artificial bee colony algorithm, decision tree classifier, elliptic curve linear regression, logistic regression, rsa algo, support vector machines

  • Updated Jun 17, 2021
  • Jupyter Notebook
Employee-Attrition-Prediction-Model

Bill Gates was once quoted as saying, "You take away our top 20 employees and we [Microsoft] become a mediocre company". This statement by Bill Gates took our attention to one of the major problems of employee attrition at workplaces. Employee attrition (turnover) causes a significant cost to any organization which may later on effect its overall efficiency. As per CompData Surveys, over the past five years, total turnover has increased from 15.1 percent to 18.5 percent. For any organization, finding a well trained and experienced employee is a complex task, but it’s even more complex to replace such employees. This not only increases the significant Human Resource (HR) cost, but also impacts the market value of an organization. Despite these facts and ground reality, there is little attention to the literature, which has been seeded to many misconceptions between HR and Employees. Therefore, the aim of this paper is to provide a framework for predicting the employee churn by analyzing the employee’s precise behaviors and attributes using classification techniques.

  • Updated Apr 24, 2020
  • Jupyter Notebook

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