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Abhivesh-Shukla/Predicting_Illnesses_through_Ensemble_Voting_Classifier_Machine-Learning

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This repository implements a machine learning-based disease prediction system using the GitHub Collaborative Disease-Symptom Dataset. It employs models like Random Forest and K-Nearest Neighbors, leveraging confusion matrices for performance evaluation. Key technologies include Python, scikit-learn, pandas, NumPy, Matplotlib, and seaborn.

active 2024-06-262024-12-13 (UTC)

Complete coverage27,257 / 27,260 hourly files (100%) · 2 absent upstream2023-08-152026-09-23 (UTC)
Events
12
Pushes
7
Pull requests
2
Issues
0
Stars
1
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 171 days from 2024-06-26 to 2024-12-13. Pushes: 7 total, peak 3 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 total, peak 1 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
Abhivesh-Shukla6600
Tam-collab3120

Recent activity

Latest issues, pull requests and releases

  • Pull request#1Tam-collab2024-06-27 12:25
  • Pull request#1Tam-collab2024-06-27 12:25

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.