Alternatives and similar repositories for hypermax

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

• ogrisel / pygbm
  Experimental Gradient Boosting Machines in Python with numba.
  ☆185Updated 6 years ago
• MLBazaar / BTB
  A simple, extensible library for developing AutoML systems
  ☆175Updated 2 years ago
• automl / ParameterImportance
  Parameter Importance Analysis Tool
  ☆77Updated 4 years ago
• levyben / DeepSuperLearner
  DeepSuperLearner - Python implementation of the deep ensemble algorithm
  ☆135Updated 7 years ago
• automl / HPOlib1.5
  ☆69Updated 5 years ago
• evhub / bbopt
  Black box hyperparameter optimization made easy.
  ☆75Updated 2 years ago
• seba-1511 / randopt
  Streamlined machine learning experiment management.
  ☆107Updated 5 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• thuijskens / scikit-hyperband
  A scikit-learn compatible implementation of hyperband
  ☆76Updated 5 years ago
• EpistasisLab / scikit-mdr
  A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
  ☆125Updated 3 months ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆183Updated 6 years ago
• AI-DI / Brancher
  A user-centered Python package for differentiable probabilistic inference
  ☆203Updated 4 years ago
• ldv1 / LinXGBoost
  Extension of the awesome XGBoost to linear models at the leaves
  ☆82Updated 6 years ago
• AIworx-Labs / chocolate
  A fully decentralized hyperparameter optimization framework
  ☆124Updated last year
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆103Updated 6 years ago
• josejimenezluna / pyGPGO
  Bayesian optimization for Python
  ☆246Updated 3 years ago
• bsharchilev / influence_boosting
  Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
  ☆68Updated last year
• aredier / trelawney
  General Interpretability Package
  ☆58Updated 2 years ago
• gdikov / hypertunity
  A toolset for black-box hyperparameter optimisation.
  ☆135Updated 5 years ago
• cgnorthcutt / hypopt
  ⏸ Parallelized hyper-param optimization with validation set, not crossval
  ☆91Updated 2 years ago
• automl / BOAH
  BOAH: Bayesian Optimization & Analysis of Hyperparameters
  ☆67Updated 5 years ago
• udellgroup / oboe
  An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
  ☆84Updated 3 years ago
• daxiongshu / rapids-ai-BBO-2nd-place-solution
  ☆71Updated 4 years ago
• zygmuntz / gaussrank
  Preparing continuous features for neural networks with GaussRank
  ☆45Updated 7 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• josephius / star-clustering
  A clustering algorithm that automatically determines the number of clusters and works without hyperparameter fine-tuning.
  ☆218Updated 4 years ago
• Jianbo-Lab / CCM
  ☆74Updated 6 years ago
• LucaAmbrogioni / Brancher
  A python library for stochastic variational inference and differentiable probabilistic programming
  ☆33Updated 6 years ago
• ili3p / HORD
  Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
  ☆115Updated 8 years ago
• facebookresearch / dagger
  Experiment orchestration
  ☆102Updated 5 years ago