Using Logistic Regression, Decision Tree, and Random Forest Machine Learning Models to Predict Leads Conversion to Enrolled Students (Paid Customers): Which is the Better Model?
Publication Date (MM-DD-YYYY)
6-24-2023
Start Date (MM-DD-YYYY)
6-24-2023 12:05 PM
End Date (MM-DD-YYYY)
6-24-2023 12:25 PM
Presentation Type
Event
Recommended Citation
(2023). Using Logistic Regression, Decision Tree, and Random Forest Machine Learning Models to Predict Leads Conversion to Enrolled Students (Paid Customers): Which is the Better Model?. Retrieved from https://fuse.franklin.edu/dsa-conf/2023/presentations/8
COinS
Jun 24th, 12:05 PM
Jun 24th, 12:25 PM
Using Logistic Regression, Decision Tree, and Random Forest Machine Learning Models to Predict Leads Conversion to Enrolled Students (Paid Customers): Which is the Better Model?
