Kyso Weekly: Issue #8
Remember to both star and promote the studies you really like!
This is the second time Patrick has been on our newsletter! In this study he looks at the main factors that lead to employee attrition, inlcuding Overtime, Marital Status, Income, Job Satisfaction and many more. First he looks at the correlation between mutiple features, before applying a more complex Random Forest Classifier. Why do employees leave their job?.
This study uses machine learning to build a POI (Person of Interest) identifier based on financial and email data made public in the aftermath of the Enron scandal of the early noughties. The goal of the project is to identify Enron employees who may have committed fraud (POIs). In total, three algorithms were tried with Gaussian Naïve Bayes coming out on top due to its precision score.
A brief but really interesting (I am a huge football fan!) statistical analysis of FIFA 18 data to determine the strongest contenders for this year's World Cup in Russia. The author looks first at interesting stats on individual players such as Value, Age and Wages, before diving into a more complex analysis of the best national squads based on FIFA 18's ratings. Finally, each squad's best current and future lineups are determined. The best part of the analysis is the conclusion, where the author makes a prediction regarding both the finalists and 3rd-place playoff opponents!!
That is all for now!! Have a great week!!