R-Shiny-Employee-Attrition-Modeling | Employee attrition is the rate at which employees

 by   nkjadhav Jupyter Notebook Version: Current License: No License

kandi X-RAY | R-Shiny-Employee-Attrition-Modeling Summary

kandi X-RAY | R-Shiny-Employee-Attrition-Modeling Summary

R-Shiny-Employee-Attrition-Modeling is a Jupyter Notebook library. R-Shiny-Employee-Attrition-Modeling has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Employee attrition is the rate at which employees leave a company. The goal of this analysis is to model employee attrition with diffrent Maine Learning Algorithms. Through this kind of analysis, we can understand not only how many employees are likely to leave, but also which employees are at the highest risk of leaving and why. Companies face significant costs for having to search for, interview and hire new employees. Although this depends on the industry, in general, a company aims to retain their employees for a significant period of time. This analysis is particularly useful if a company wants to lower attrition levels but is unsure of the source of the problem.
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              R-Shiny-Employee-Attrition-Modeling has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are no watchers for this library.
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              It had no major release in the last 6 months.
              R-Shiny-Employee-Attrition-Modeling has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of R-Shiny-Employee-Attrition-Modeling is current.

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              R-Shiny-Employee-Attrition-Modeling has no bugs reported.

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              R-Shiny-Employee-Attrition-Modeling has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              R-Shiny-Employee-Attrition-Modeling releases are not available. You will need to build from source code and install.

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