#HRAnalytics
#PeopleAnanlytics
#ExploratoryDataAnalysis
#R
#RshinyApp
#AssociationRuleMiningAlgorithm
Every Organization takes a hit when thier talent leaves them. To answer this question of "Why?", institutions spend thousands of dollars. I have created an app that provides a reasoning of why an employee decides to leave our beloved organization and why an employee decides to stick around for years.
The link to the Rshiny Webapp: Link
This app allows you to.....
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look at the original dataset and the discretized data that was provided as an input to the ML Algorithm
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see the summary statistics of each attribute of the dataset
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Exploratory Data Analysis : Data Visualization
Univariate Analysis - binning distributions of discretized data (Horizontal Bar plot). Univariate Analysis - distributions with summary statistics(Mean, Median, Standard Deviation, Spread, Percentile). These were presented in 3 types: Histograms, Boxplots and Density Plots. Bivariate Analysis - scatter plot of any two attributes, a parameter control is provided to change the inputs of the graph. -
Finally, The reasoning behind the attrition was explained by the Association Rule Mining Algorithm. The user has the control to change the parameters to make more confident output and make better informed strategic decisions accordingly. Attrition is either Yes or No that is Employee Still employed or Left the organization respectively.
