4. Open and run `main.ipynb` to train the classification models for attrition prediction and analyze the importance of predictor variables. 4. Open and run `employee-attrition-prediction.ipynb` to train the classification models for attrition prediction and analyze the importance of predictor variable...
In this study we seek to predict employee attrition with KNN clustering and Naive Bayes, and to predict employee salary using multiple linear regression - jlaskow/Employee-Demographics-for-FritoLay
Github (Microsoft): Data Science Accelerator - Employee Attrition Prediction with Sentiment Analysis Related AzureDSVM: a new R package for elastic use of the Azure Data Science Virtual Machine by Le Zhang (Data Scientist, Microsoft) and Graham Williams (Director of Data Science, Microsoft) The Az...
The data science language R is a convenient tool for performing HR churn prediction analysis. A lightweight data science accelerator that demonstrates the process of predicting employee attrition is shared in thisGithub repository. The walk-through basically shows cutting-edge machine learning and text ...
Developed a logistic regression model to predict employee attrition/churn rate and identify factors that contribute to employee retention using Python. - nikitia/logistic_regression
A command line utility for predicting whether employees are at risk of voluntarily leaving their employment. To make predictions, AtPred uses a Support Vector Machine trained against publicly available IBM HR employee attrition data. - MLBC-lab/AtPred