Essay Available:
Pages:
1 pages/≈275 words
Sources:
0
Style:
APA
Subject:
IT & Computer Science
Type:
Essay
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
$ 6.08
Topic:
Production Turnover Report Template
Essay Instructions:
Critical Elements
Specify the business department using this model
Create a descriptive name for the business project being deployed
Describe the project in a short paragraph
Describe the model baselines for the project, including the expected accuracy, lift,
and receiver operating characteristic (ROC) from the training and verification data
Document your observations regarding model performance as data volume increases
Provide additional project comments, such as the outputs the business users will use
Essay Sample Content Preview:
Production Turnover Report Template
Human Resource Department
A Predictive Model to Provide a Solution for Employee Attrition
GE is focused on reducing employee attrition because it is costly; replacing an employee is equivalent to 80% of the employee’s income. GE invests a significant amount of time and money in training new employees in order to remain competitive in the job market. As a result, an effective model for identifying employees on the verge of leaving is required. One possible solution is to build a predictive model using historical data to assess employee profiles and classify them based on their potential to churn. Therefore, this project sought to develop a classification model that can predict between employees who are likely to churn. These capabilities will allow the company to develop intervention measures before an employee is lost. As a result, a baseline model was built by utilizing a Random Forest algorithm. Appropriate data cleaning and data preparation w...
Human Resource Department
A Predictive Model to Provide a Solution for Employee Attrition
GE is focused on reducing employee attrition because it is costly; replacing an employee is equivalent to 80% of the employee’s income. GE invests a significant amount of time and money in training new employees in order to remain competitive in the job market. As a result, an effective model for identifying employees on the verge of leaving is required. One possible solution is to build a predictive model using historical data to assess employee profiles and classify them based on their potential to churn. Therefore, this project sought to develop a classification model that can predict between employees who are likely to churn. These capabilities will allow the company to develop intervention measures before an employee is lost. As a result, a baseline model was built by utilizing a Random Forest algorithm. Appropriate data cleaning and data preparation w...
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