Alternatives and similar repositories for hpbandster-sklearn:

Users that are interested in hpbandster-sklearn are comparing it to the libraries listed below

• pyensemble / wildwood
  Advanced random forest methods in Python
  ☆57Updated last year
• PySloth / pysloth
  A Python Package for Probabilistic Prediction
  ☆22Updated 3 years ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated last year
• felipeangelimvieira / prophetverse
  A multiverse of Prophet models for timeseries
  ☆43Updated this week
• MaxHalford / starboost
  Gradient boosting on steroids
  ☆27Updated 8 months ago
• jdb78 / lipo
  Global, derivative-free optimization for hyperparameter tuning
  ☆42Updated 2 years ago
• lorentzenchr / model-diagnostics
  Tools for diagnostics and assessment of (machine learning) models
  ☆34Updated last week
• jrbourbeau / dask-optuna
  Scale Optuna with Dask
  ☆35Updated 4 years ago
• StatMixedML / Py-BoostLSS
  An extension of Py-Boost to probabilistic modelling
  ☆21Updated 2 years ago
• StatMixedML / DGBM
  Distributional Gradient Boosting Machines
  ☆27Updated 2 years ago
• JohnGoertz / Gumbi
  Gaussian Process Model Building Interface
  ☆50Updated this week
• Quantco / tabmat
  Efficient matrix representations for working with tabular data
  ☆120Updated last week
• DanaJomar / PyALE
  ALE Plots with python
  ☆61Updated 11 months ago
• eserie / wax-ml
  A Python library for machine-learning and feedback loops on streaming data
  ☆60Updated last year
• parrt / stratx
  stratx is a library for A Stratification Approach to Partial Dependence for Codependent Variables
  ☆65Updated 10 months ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• polsys / ennemi
  Easy Nearest Neighbor Estimation of Mutual Information
  ☆36Updated 4 months ago
• CDonnerer / xgboost-distribution
  Probabilistic prediction with XGBoost.
  ☆106Updated 3 weeks ago
• nmdwolf / ValidPredictionIntervals
  Contains the code to run the different models considered in the paper "Valid prediction intervals for regression problems"
  ☆19Updated 2 years ago
• mjhajharia / pydata21
  Pydata talk - Football Analytics Using Hierarchical Bayesian Models in PyMC
  ☆26Updated 3 years ago
• rick12000 / confopt
  A Library for Conformal Hyperparameter Tuning
  ☆29Updated this week
• ralphhaygood / sklearn-gbmi
  scikit-learn gradient-boosting-model interactions
  ☆25Updated last year
• sdpython / mlinsights
  Extends scikit-learn with new models, transformers, metrics, plotting.
  ☆72Updated 6 months ago
• sktime / skbase
  Base classes for creating scikit-learn-like parametric objects, and tools for working with them.
  ☆23Updated last week
• jasperroebroek / sklearn-quantile
  ☆21Updated last week
• erdogant / hgboost
  hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…
  ☆61Updated last week
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆64Updated last week
• nickfrosst / neural_additive_models
  stand alone Neural Additive Models, forked from google-reasearch for easy import to colab
  ☆27Updated 4 years ago
• microsoft / CBM
  Cyclic Boosting Machines - an explainable supervised machine learning algorithm
  ☆60Updated 6 months ago
• manuel-calzolari / shapicant
  Feature selection package based on SHAP and target permutation, for pandas and Spark
  ☆30Updated 3 years ago