Journal: Status Report on the Random Forest Technique

Journal: Status Report
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Journal: Status Report
The random forest technique is a single tree model with a high predictive power since it leverages the predictive power of many weak trees to come up with a fairly accurate prediction. The model’s enhanced predictive performance was tested using a confusion matrix in an experiment aimed at determining turnover rates in a company (whether an employee would churn or not). From the results obtained, the model was able to predict with 95 percent accuracy for a group of 213 employees who churned and with 22 percent accuracy for a group of 41 employees who churned. I plan on promoting the random forest technique model design to producti...