PREDICTION OF EMPLOYEE ATTRITION USING DATAMINING
| Autor: | V. V. Sivaramaraju, R. Shiva Shankar, K Vssr Murthy, J. Rajanikanth |
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| Rok vydání: | 2018 |
| Předmět: |
Actuarial science
ComputingMilieux_THECOMPUTINGPROFESSION business.industry Decision tree ComputerApplications_COMPUTERSINOTHERSYSTEMS Feature selection medicine.disease Logistic regression Random forest Naive Bayes classifier ComputingMilieux_COMPUTERSANDEDUCATION Remuneration medicine Attrition Business Human resources ComputingMilieux_MISCELLANEOUS |
| Zdroj: | 2018 ieee international conference on system, computation, automation and networking (icscan). |
| Popis: | Now a day’s Employee Attrition prediction become a major problem in the organizations. Employee Attrition is a big issue for the organizations specially when trained, technical and key employees leave for a better opportunity from the organization. This results in financial loss to replace a trained employee. Therefore, we use the current and past employee data to analyze the common reasons for employee attrition or attrition. For the prevention of employee attrition, we applied a well known classification methods, that is, Decision tree, Logistic Regression, SVM, KNN, Random Forest, Naive bayes methods on the human resource data. For this we implement feature selection method on the data and analysis the results to prevent employee attrition. This is helpful to companies to predict employee attrition, and also helpful to their economic growth by reducing their human resource cost. |
| Databáze: | OpenAIRE |
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