Skip to content

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

active 2023-08-162026-05-03 (UTC)

Complete coverage26,466 / 26,466 hourly files (100%) · 2 absent upstream2023-08-152026-08-21 (UTC)
Events
482
Pushes
53
Pull requests
21
Issues
75
Stars
205
Forks
32

Activity over time

Daily event counts in the loaded window

Line chart, 992 days from 2023-08-16 to 2026-05-03. Pushes: 53 total, peak 9 in a day. Pull requests: 21 total, peak 8 in a day. Issues: 75 total, peak 8 in a day. Comments: 95 total, peak 8 in a day. Stars: 205 total, peak 6 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
AutoViML142531246
arturdaraujo160011
reza161515017
mfansler9005
chinmay70165021
GDGauravDutta5002
THEFZNKHAN4022
ecederstrand4002
Buedenbender3002
gps19383001
grandrew3001
lvfmc853001
ferrotem3002
jonathanhexner2001
sungla55guy2000
AaadityaG2011
deuf-projects2000
sideshot2001
jmakov2000
rsesha2002

Recent activity

Latest issues, pull requests and releases

  • Issue comment#130AutoViML2025-08-06 00:55
    Compatibility with xgboost > 2
  • Issue comment#131AutoViML2025-08-06 00:55
    Feature selection + hyperparameter tunning?
  • Issue#131AutoViML2025-08-06 00:55
    Feature selection + hyperparameter tunning?
  • Issue#131ogreyesp2025-07-28 14:26
    Feature selection + hyperparameter tunning?
  • Issue#129AutoViML2025-06-12 00:33
    problems using featurewiz in a pipeline
  • Issue comment#129AutoViML2025-03-30 12:49
    problems using featurewiz in a pipeline
  • Issue#129sdaza2025-03-28 11:19
    problems using featurewiz in a pipeline
  • Issue#128AutoViML2025-02-12 01:42
    making parallel most part of the featurwize
  • Issue#114AutoViML2025-01-30 01:22
    Cannot clone object FeatureWiz...as the constructor either does not set or modifies parameter auto_encoder
  • Issue#115AutoViML2025-01-30 01:21
    "TypeDict" error when importing Featurewiz class...
  • Issue#116AutoViML2025-01-30 01:21
    Installation Error
  • Issue#120AutoViML2025-01-30 01:21
    Update requirements packages
  • Issue#122AutoViML2025-01-30 01:21
    Update xgboost in the requirements to at least 1.7.6
  • Issue#125AutoViML2025-01-30 01:20
    Update requirements packages; sklearn 1.2.2
  • Issue#126AutoViML2025-01-30 01:20
    Parameter to control xgboost core_num
  • Issue#127AutoViML2025-01-30 01:20
    lazytransform removed from requirements
  • Issue comment#127AutoViML2025-01-30 01:20
    lazytransform removed from requirements
  • Issue comment#128AutoViML2025-01-30 01:19
    making parallel most part of the featurwize
  • Issue comment#118mfansler2025-01-29 16:48
    Optional components should emit warnings when dependencies are absent
  • Issue comment#119mfansler2025-01-29 16:48
    Cannot load `tensorflow.keras.layers`
  • Issue#119mfansler2025-01-29 16:48
    Cannot load `tensorflow.keras.layers`
  • Issue comment#117mfansler2025-01-29 16:47
    Undeclared requirement: `imbalanced-learn`
  • Issue comment#128reza16152025-01-29 16:07
    making parallel most part of the featurwize
  • Issue comment#128AutoViML2025-01-29 15:12
    making parallel most part of the featurwize
  • Issue comment#127AutoViML2025-01-29 15:11
    lazytransform removed from requirements

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 205 stars here means stars gained during the window, not the repo's star count.