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Employee Analytics - Create Predictive Models - R Studio Assignment Help
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Internal Code : 3HIG
Create predictive models : Random Forest and Decision Tree models covering below
Decision Tree: Visualisation, Confusion matrix and accuracy
Random Forest: Initial Model, prediction and confusion matrix, error rate, tune the model, fit the model, Predictions and Confusion Matrix After Tuning, Random Forest Feature Importance
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Task: R Studio: Employee Analytics- Employees are the biggest assets of an organization – customers come second. Being able to hire and retain the right talent enhances a company’s reputation.
- Employee turnover (attrition) is a major cost to an organization, and predicting turnover is at the forefront of needs of Human Resources (HR) in many organizations.
- The problem of employee turnover has negative impacts on issues ranging from work place morale and productivity, to disruptions in project continuity.
- There are several instances where employees quit their organizations without giving any previous signals. With the exception of the human factors it is possible to notice indicators or signs, when employees are contemplating their exit.
- Identifying high performing employees with a plan to retain them is as important as avoiding overspend on those employees with low probability of staying with the organisation.
Create predictive models : Random Forest and Decision Tree models covering below
Decision Tree: Visualisation, Confusion matrix and accuracy
Random Forest: Initial Model, prediction and confusion matrix, error rate, tune the model, fit the model, Predictions and Confusion Matrix After Tuning, Random Forest Feature Importance
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