sibirbil/LESS
Learning with Subset Stacking
This algorithm helps data scientists and machine learning engineers build more robust predictive models. It takes your existing dataset, trains many specialized models on different parts of it, and then combines their insights for a final, powerful prediction. The output is a more accurate and reliable forecast for your target variable.
Use this if you are a machine learning practitioner looking for an advanced method to improve the accuracy and robustness of your regression models.
Not ideal if you need a simple, interpretable model or are working with very small datasets where ensemble methods might overfit.
Stars
24
Forks
4
Language
Python
License
MIT
Category
Last pushed
Nov 22, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sibirbil/LESS"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
iamDecode/sklearn-pmml-model
A library to parse and convert PMML models into Scikit-learn estimators.
vecxoz/vecstack
Python package for stacking (machine learning technique)
yzhao062/combo
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
flennerhag/mlens
ML-Ensemble – high performance ensemble learning
aws-samples/aws-machine-learning-university-dte
Machine Learning University: Decision Trees and Ensemble Methods