Alternatives and similar repositories for xgboost-distribution:

Users that are interested in xgboost-distribution are comparing it to the libraries listed below

• StatMixedML / LightGBMLSS
  An extension of LightGBM to probabilistic modelling
  ☆289Updated 7 months ago
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆222Updated last month
• elephaint / pgbm
  Probabilistic Gradient Boosting Machines
  ☆144Updated 11 months ago
• superlinear-ai / conformal-tights
  👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
  ☆90Updated last week
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated 11 months ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆116Updated last year
• rick12000 / confopt
  A Library for Conformal Hyperparameter Tuning
  ☆28Updated 2 weeks ago
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆202Updated 8 months ago
• StatMixedML / CatBoostLSS
  An extension of CatBoost to probabilistic modelling
  ☆142Updated last year
• carlomazzaferro / scikit-hts
  Hierarchical Time Series Forecasting with a familiar API
  ☆223Updated last year
• tblume1992 / ThymeBoost
  Forecasting with Gradient Boosted Time Series Decomposition
  ☆191Updated last year
• ykwon0407 / WeightedSHAP
  WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)
  ☆160Updated 2 years ago
• pymc-devs / pymc-bart
  ☆100Updated this week
• erdogant / hgboost
  hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…
  ☆61Updated 3 months ago
• pyro-ppl / Pyro-M5-Starter-Kit
  Learn Pyro through the M5 forecasting competition
  ☆84Updated 4 years ago
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆136Updated 4 months ago
• StatMixedML / XGBoostLSS
  An extension of XGBoost to probabilistic modelling
  ☆573Updated 6 months ago
• JakeColtman / bartpy
  Bayesian Additive Regression Trees For Python
  ☆219Updated last year
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆67Updated last year
• Blue-Yonder-OSS / cyclic-boosting
  implementation of Cyclic Boosting machine learning algorithms
  ☆89Updated 4 months ago
• cerlymarco / tspiral
  A python package for time series forecasting with scikit-learn estimators.
  ☆160Updated 9 months ago
• sktime / skpro
  A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
  ☆254Updated this week
• salesforce / online_conformal
  Methods for online conformal prediction.
  ☆108Updated last year
• Nixtla / tsfeatures
  Calculates various features from time series data. Python implementation of the R package tsfeatures.
  ☆378Updated 8 months ago
• Nixtla / utilsforecast
  ☆50Updated last month
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆59Updated this week
• cerlymarco / linear-tree
  A python library to build Model Trees with Linear Models at the leaves.
  ☆368Updated 5 months ago
• brendanhasz / probflow
  A Python package for building Bayesian models with TensorFlow or PyTorch
  ☆171Updated 2 years ago
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 3 years ago
• astrogilda / tsbootstrap
  tsbootstrap: generate bootstrapped time series samples in Python
  ☆76Updated last month