Alternatives and similar repositories for PiML-Toolbox

Users that are interested in PiML-Toolbox are comparing it to the libraries listed below

• scikit-learn-contrib / MAPIE
  A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
  ☆1,503Updated this week
• csinva / imodels
  Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
  ☆1,563Updated last month
• feature-engine / feature_engine
  Feature engineering package with sklearn like functionality
  ☆2,177Updated last week
• oegedijk / explainerdashboard
  Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
  ☆2,465Updated 5 months ago
• MAIF / shapash
  🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
  ☆3,111Updated last month
• alteryx / evalml
  EvalML is an AutoML library written in python.
  ☆841Updated this week
• skrub-data / skrub
  Machine learning with dataframes
  ☆1,541Updated this week
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆584Updated last year
• NannyML / nannyml
  nannyml: post-deployment data science in python
  ☆2,121Updated 5 months ago
• henrikbostrom / crepes
  Python package for conformal prediction
  ☆549Updated 3 months ago
• AutoViML / featurewiz
  Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…
  ☆676Updated 10 months ago
• facebookresearch / balance
  The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to s…
  ☆733Updated this week
• pymc-labs / CausalPy
  A Python package for causal inference in quasi-experimental settings
  ☆1,083Updated this week
• functime-org / functime
  Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
  ☆1,164Updated 3 months ago
• mljar / supertree
  Visualize decision trees in Python
  ☆521Updated 10 months ago
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆641Updated last year
• linkedin / FastTreeSHAP
  Fast SHAP value computation for interpreting tree-based models
  ☆550Updated 2 years ago
• Nixtla / mlforecast
  Scalable machine 🤖 learning for time series forecasting.
  ☆1,137Updated this week
• 8080labs / ppscore
  Predictive Power Score (PPS) in Python
  ☆1,170Updated 3 months ago
• BCG-X-Official / facet
  Human-explainable AI.
  ☆528Updated 3 months ago
• koaning / scikit-lego
  Extra blocks for scikit-learn pipelines.
  ☆1,374Updated last month
• mmschlk / shapiq
  Shapley Interactions and Shapley Values for Machine Learning
  ☆666Updated 2 weeks ago
• valeman / Awesome_CatBoost
  The repository to showcase the best framework for tabular data - the Awesome CatBoost
  ☆280Updated 4 months ago
• NannyML / The-Little-Book-of-ML-Metrics
  The book every data scientist needs on their desk.
  ☆992Updated 3 months ago
• AutoViML / Auto_TS
  Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…
  ☆764Updated last year
• PacktPublishing / Interpretable-Machine-Learning-with-Python
  Interpretable Machine Learning with Python, published by Packt
  ☆477Updated 3 weeks ago
• Nixtla / hierarchicalforecast
  Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
  ☆723Updated this week
• smazzanti / mrmr
  mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
  ☆617Updated last year
• skforecast / skforecast
  Time series forecasting with machine learning models
  ☆1,426Updated last week
• abhishekkrthakur / autoxgb
  XGBoost + Optuna
  ☆728Updated last year