vecstack
A Python package for stacking (stacked generalization) with both functional and scikit-learn compatible APIs.
What is vecstack?
Vecstack is a Python package for implementing stacking (stacked generalization), a machine learning technique that combines multiple models by using their predictions as features for a higher-level model. It solves the problem of improving predictive performance through ensembling while providing both a lightweight functional API and a fully scikit-learn compatible API for flexibility.
Data scientists, machine learning engineers, and Kaggle competitors who need to build robust ensemble models and want efficient, scalable stacking implementations.
Developers choose Vecstack for its dual API approach—offering maximum memory efficiency for competitions and full scikit-learn integration for production pipelines—along with extensive customization options and detailed documentation.
Overview
Python package for stacking (machine learning technique)
Use Cases
Best For
- Building ensemble models for Kaggle competitions with minimal RAM usage
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