simonprovost/Auto-Sklong
☂️ Auto-Scikit-Longitudinal (Auto-Sklong) is an automated machine learning (AutoML) library designed to analyse longitudinal data (Classification tasks focussed as of today) using various search methods. Namely, Bayesian Optimisation via SMAC3, Asynchronous Successive Halving, Evolutionary Algorithms, and Random Search via GAMA
This tool helps researchers and data scientists analyze longitudinal data, which is like a time-lapse of observations on the same subjects over time (e.g., patient health metrics annually). It takes your longitudinal dataset and automatically finds the best machine learning model to classify future outcomes. The output is a classification report, telling you how well the model predicts.
No commits in the last 6 months. Available on PyPI.
Use this if you have longitudinal data and need to predict categorical outcomes without manually experimenting with countless machine learning models and their settings.
Not ideal if your data is not longitudinal (i.e., you only have a single snapshot in time for each subject) or if you need to predict continuous values instead of categories.
Stars
43
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 15, 2025
Commits (30d)
0
Dependencies
12
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/simonprovost/Auto-Sklong"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
process-intelligence-solutions/pm4py
Official public repository for PM4Py (Process Mining for Python) — an open-source library for...
autogluon/autogluon
Fast and Accurate ML in 3 Lines of Code
microsoft/FLAML
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
shankarpandala/lazypredict
Lazy Predict help build a lot of basic models without much code and helps understand which...
aimclub/FEDOT
Automated modeling and machine learning framework FEDOT