Vecstack

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vecstack is an Open Source & Models tool that provides a Python package for stacking (stacked generalization) in machine learning. It offers both a lightweight functional API and a fully scikit-learn compatible API for automating OOF computation, prediction, and bagging.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is vecstack?

vecstack is a Python package designed for implementing stacking, a powerful machine learning ensembling technique also known as stacked generalization. It provides a convenient way to automate out-of-fold (OOF) computation, prediction, and bagging across various models. The package features a minimalistic functional API for quick integration and a standardized scikit-learn compatible API, allowing for seamless use within existing scikit-learn pipelines, including multilevel stacking with `sklearn.pipeline.Pipeline` and `FeatureUnion`. It supports classification and regression tasks, handles class labels or probabilities, and allows for user-defined metrics and transformations. vecstack is RAM-friendly and can automatically save stacked features and hyperparameters, making it suitable for competitive machine learning environments like Kaggle.

Best used for

Ideal for data scientists and developers who need to implement advanced machine learning ensembling techniques, automate out-of-fold predictions, and integrate stacking into scikit-learn pipelines. Especially valuable for competitive machine learning scenarios like Kaggle, where performance optimization is crucial.

Common actions

perform stacking

automate machine learning

improve model performance

ensemble models

"AI Agents"github copilotface swappingworkflowslow-code/no-codeopen-sourcecollaborationautomated workflowdeepfake

Capabilities

Key features

Stacking (stacked generalization)
Functional API
Scikit-learn API
Automate OOF computation
RAM-friendly
Save stacked features
Multilevel stacking

Target Audience

data scientistdeveloper

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What is the primary purpose of the vecstack package?

The vecstack package is designed to simplify and automate the process of stacking (stacked generalization), a machine learning ensembling technique. It allows users to combine multiple models to improve predictive performance by using their predictions as features for a second-level model, handling complex cross-validation procedures efficiently.

Does vecstack support both functional and scikit-learn APIs?

Yes, vecstack offers both a lightweight functional API for quick and minimalistic implementation, and a fully compatible scikit-learn API. The scikit-learn API provides a `StackingTransformer` class, enabling seamless integration into `sklearn.pipeline.Pipeline` for multilevel stacking and other scikit-learn functionalities.

What types of machine learning tasks can vecstack be used for?

vecstack can be used for both classification and regression tasks. It supports predicting class labels or probabilities in classification and allows for the application of any user-defined metric or transformations for target and prediction values, making it versatile for various machine learning problems.

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Also listed in

This tool also appears in

Research & Education › Scientific Computing Data & Analytics › Statistical & Scientific

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