In this project, we used various algorithms like k-nearest neighbors, logistic regression, discriminant analysis, etc. to perform user segmentation for a financial institution. The desired outcome is to have a reliable and fast classifier to support decision-makers in conceding (or not) a line of credit to future credit card holders according to their profile. The metadata has been changed to meaningless symbols to protect the confidentiality and all programming was done in MATLAB.
-
Notifications
You must be signed in to change notification settings - Fork 1
rdamatta/customer-classification
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
User segmentation using a sort of classifiers (some quite uncommon like the Fuzzy K-Nearest Neighbours).
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published