This is a machine learning project using the Decision Tree algorithm to predict the loyalty of potential customers based on household income, household size, education level, and gender. Trains and tests the data, returns an accuracy score, and makes a prediction with inputted (feel free to change it up!) data on a made up customer.
active 2023-09-11 → 2023-09-11 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2023-09-11 to 2023-09-11. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| drewbeno1 | 1 | 1 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.