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This project classifies near-Earth asteroids as hazardous or non-hazardous using machine learning. The dataset from NASA’s NeoWs includes asteroid size, velocity, orbit, and approach data. The model preprocesses data, selects key features, and trains classifiers to predict hazards. Results help in asteroid threat detection for planetary defense. 🚀

active 2025-03-272025-05-15 (UTC)

Complete coverage26,731 / 26,731 hourly files (100%) · 2 absent upstream2023-08-152026-09-01 (UTC)
Events
114
Pushes
94
Pull requests
6
Issues
6
Stars
1
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 50 days from 2025-03-27 to 2025-05-15. Pushes: 94 total, peak 20 in a day. Pull requests: 6 total, peak 4 in a day. Issues: 6 total, peak 3 in a day. Comments: 1 total, peak 1 in a day. Stars: 1 total, peak 1 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
PriyanshuRao-code585300
Armaan0805403261
ry17296600
CSL7303300

Recent activity

Latest issues, pull requests and releases

  • Issue#5PriyanshuRao-code2025-04-26 09:19
    enhancement: Add flexible Data Preprocessing Techniques for Experimentation
  • Issue#7PriyanshuRao-code2025-04-26 09:19
    Add Visualizations to Compare Model Performance Across Different Preprocessing Techniques
  • Issue comment#4Armaan08052025-04-10 19:41
    feat: Add Random Forest Model in Supervised Learning Module
  • Issue#4Armaan08052025-04-10 19:41
    feat: Add Random Forest Model in Supervised Learning Module
  • Issue#8PriyanshuRao-code2025-04-09 21:02
    Add Model Epoch vs Loss Graphs to Visualize Model Training Performance
  • Issue#7PriyanshuRao-code2025-04-09 20:58
    Add Visualizations to Compare Model Performance Across Different Preprocessing Techniques
  • Issue#4PriyanshuRao-code2025-04-09 20:30
    feat: Add Random Forest Model in Supervised Learning Module
  • Pull request#3Armaan08052025-04-03 17:45
  • Pull request#3Armaan08052025-04-03 17:44
  • Pull request#2Armaan08052025-04-03 16:13
  • Pull request#2Armaan08052025-04-03 16:12
  • Pull request#1Armaan08052025-03-29 19:15
  • Pull request#1Armaan08052025-03-29 19:14

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.