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carrickcheah/predict_customer_churn

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This project focuses on predicting customer churn, segmenting customers, and analyzing order patterns using data mining techniques. By leveraging classification, clustering, and association rule mining, the project aims to enhance decision-making, improve customer retention, and optimize marketing strategies for an e-commerce platform.

active 2024-10-18 → 2024-11-26 (UTC)

Complete coverage27,992 / 27,992 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-24 (UTC)
Events
6
Pushes
4
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 40 days from 2024-10-18 to 2024-11-26. Pushes: 4 total, peak 4 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
carrickcheah4400

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.