Alternatives and similar repositories for XGBoostLSS

Users that are interested in XGBoostLSS are comparing it to the libraries listed below

• StatMixedML / LightGBMLSS
  An extension of LightGBM to probabilistic modelling
  ☆345Updated this week
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆638Updated last year
• fabsig / GPBoost
  Combining tree-boosting with Gaussian process and mixed effects models
  ☆642Updated last week
• AnotherSamWilson / miceforest
  Multiple Imputation with LightGBM in Python
  ☆396Updated last month
• Nixtla / tsfeatures
  Calculates various features from time series data. Python implementation of the R package tsfeatures.
  ☆435Updated last year
• cerlymarco / linear-tree
  A python library to build Model Trees with Linear Models at the leaves.
  ☆387Updated last year
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆249Updated last week
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆211Updated last month
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆581Updated last year
• tblume1992 / ThymeBoost
  Forecasting with Gradient Boosted Time Series Decomposition
  ☆197Updated 2 years ago
• CDonnerer / xgboost-distribution
  Probabilistic prediction with XGBoost.
  ☆120Updated 8 months ago
• ThomasBury / arfs
  All Relevant Feature Selection
  ☆142Updated 8 months ago
• scikit-learn-contrib / MAPIE
  A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
  ☆1,493Updated this week
• guillermo-navas-palencia / optbinning
  Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…
  ☆501Updated last month
• Nixtla / hierarchicalforecast
  Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
  ☆716Updated last week
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆532Updated 8 months ago
• christophM / rulefit
  Python implementation of the rulefit algorithm
  ☆425Updated 2 years ago
• stanfordmlgroup / ngboost
  Natural Gradient Boosting for Probabilistic Prediction
  ☆1,807Updated last week
• loft-br / xgboost-survival-embeddings
  Improving XGBoost survival analysis with embeddings and debiased estimators
  ☆342Updated last year
• linkedin / FastTreeSHAP
  Fast SHAP value computation for interpreting tree-based models
  ☆546Updated 2 years ago
• blent-ai / ALEPython
  Python Accumulated Local Effects package
  ☆169Updated 2 years ago
• Mcompetitions / M5-methods
  Data, Benchmarks, and methods submitted to the M5 forecasting competition
  ☆647Updated 2 years 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…
  ☆675Updated 9 months ago
• kearnz / autoimpute
  Python package for Imputation Methods
  ☆251Updated last year
• MIDASverse / MIDASpy
  Python package for missing-data imputation with deep learning
  ☆156Updated last year
• carlomazzaferro / scikit-hts
  Hierarchical Time Series Forecasting with a familiar API
  ☆225Updated 2 years 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
• elephaint / pgbm
  Probabilistic Gradient Boosting Machines
  ☆157Updated last year
• predict-idlab / tsflex
  Flexible time series feature extraction & processing
  ☆436Updated last year
• smazzanti / mrmr
  mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
  ☆617Updated last year