LIVE DataTalk on HR Analytics Tonight: Using Machine Learning to Predict Employee Turnover
Written by Matt Dancho on October 26, 2017
Tonight at 7PM EST, we will be giving a LIVE #DataTalk on Using Machine Learning to Predict Employee Turnover. 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. Until now the mainstream approach has been to use logistic regression or survival curves to model employee attrition. However, with advancements in machine learning (ML), we can now get both better predictive performance and better explanations of what critical features are linked to employee attrition. We used two cutting edge techniques: the
h2o package’s new FREE automatic machine learning algorithm,
h2o.automl(), to develop a predictive model that is in the same ballpark as commercial products in terms of ML accuracy. Then we used the new
lime package that enables breakdown of complex, black-box machine learning models into variable importance plots. The talk will cover HR Analytics and how we used R, H2O, and LIME to predict employee turnover.
The DataTalk is FREE and LIVE. You can sign up for a reminder on Experian DataLab’s website here: Machine Learning for Recruitment & Reducing Employee Attrition.
- Analysis: We used H2O and LIME to predict employee turnover. Here’s the LIME feature importance visualization.
Time: 7PM EST
Venue: Facebook LIVE Event - Signup for a reminder here
Speaker: Matt Dancho, Founder of Business Science, creator of
tidyquant, and business science guru.
Topic and Code: Machine Learning for Recruitment & Reducing Employee Attrition. The original post got 700+ LinkedIn Shares and you can view the code and articles here:
You can follow the fun on twitter:
More details can be found on Experian DataLabs Website here.
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