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This project aims to detect fraudulent transactions from credit card data using machine learning models. We explore various preprocessing techniques, handle imbalanced datasets, train different models, and evaluate their performance through metrics and visualizations.

active 2024-03-042024-03-04 (UTC)

Complete coverage27,145 / 27,147 hourly files (100%) · 2 absent upstream2023-08-152026-09-19 (UTC)
Events
17
Pushes
13
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2024-03-04 to 2024-03-04. Pushes: 13 total, peak 13 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

ContributorContributionsPushesPRsComments
HimelDGupta131300

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.