Powershap Alternatives

Similar projects and alternatives to powershap

cascade

9 16 9.5 Python powershap VS cascade

Lightweight and modular MLOps library targeted at small teams or individuals (by Oxid15)
evalml

2 709 8.8 Python powershap VS evalml

EvalML is an AutoML library written in python.
InfluxDB

www.influxdata.com sponsored

Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
NVTabular

1 1,004 5.5 Python powershap VS NVTabular

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
upgini

16 290 9.1 Python powershap VS upgini

Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs
scikit-learn

81 58,046 9.9 Python powershap VS scikit-learn

scikit-learn: machine learning in Python
Sklearn-genetic-opt

6 271 4.6 Python powershap VS Sklearn-genetic-opt

ML hyperparameters tuning and features selection, using evolutionary algorithms.
mljar-supervised

51 2,929 8.5 Python powershap VS mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
WorkOS

workos.com sponsored

The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better powershap alternative or higher similarity.

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[R] PowerShap: A power-full Shapley feature selection method.
1 project | /r/MachineLearning | 20 Jun 2022

We are glad to present our novel shap-based wrapper feature selection method called PowerShap! This method uses statistical hypothesis testing and power calculations on Shapley values, enabling fast and intuitive wrapper-based feature selection. The complete library and methods are fully compatible with Sklearn, LightGBM, CatBoost, and more are coming in further following releases and the library can be found here: https://github.com/predict-idlab/powershap! The library is open-source and usable out-of-the-box as shown in the video!