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Functions and helpers for machine learning algorithms in R

active 2023-09-012024-01-12 (UTC)

Complete coverage26,458 / 26,458 hourly files (100%) · 2 absent upstream2023-08-152026-08-21 (UTC)
Events
51
Pushes
17
Pull requests
10
Issues
8
Stars
0
Forks
1

Activity over time

Daily event counts in the loaded window

Line chart, 134 days from 2023-09-01 to 2024-01-12. Pushes: 17 total, peak 4 in a day. Pull requests: 10 total, peak 4 in a day. Issues: 8 total, peak 5 in a day. Comments: 2 total, peak 1 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
jmaspons3616102
github-actions[bot]1100

Recent activity

Latest issues, pull requests and releases

  • Pull request#13jmaspons2023-12-12 09:20
  • Pull request#13jmaspons2023-12-12 09:20
  • Pull request#12jmaspons2023-10-11 17:12
  • Issue comment#5jmaspons2023-10-11 17:11
    SHAP
  • Pull request#12jmaspons2023-10-11 17:11
  • Issue#7jmaspons2023-10-09 09:55
    Implement pipe with xgboost
  • Issue comment#7jmaspons2023-10-09 09:55
    Implement pipe with xgboost
  • Pull request#11jmaspons2023-10-06 09:54
  • Pull request#11jmaspons2023-10-06 09:54
  • Issue#9jmaspons2023-09-28 16:21
    Fix warning in keras about missing weighted_metrics
  • Pull request#10jmaspons2023-09-28 16:21
  • Pull request#10jmaspons2023-09-28 16:20
  • Issue#9jmaspons2023-09-28 16:18
    Fix warning in keras about missing weighted_metrics
  • Issue#8jmaspons2023-09-28 10:56
    Factor out common function from *_helpers.R
  • Issue#7jmaspons2023-09-28 10:56
    Implement pipe with xgboost
  • Issue#4jmaspons2023-09-28 10:54
    Implement pipes using random forest method
  • Pull request#6jmaspons2023-09-28 10:54
  • Pull request#6jmaspons2023-09-28 10:54
  • Issue#5jmaspons2023-09-18 10:21
    SHAP
  • Issue#4jmaspons2023-09-18 10:20
    Implement pipes using random forest method

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.