Alternatives and similar repositories for ParameterImportance

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

• automl / HPOlib1.5
  ☆69Updated 5 years ago
• lacava / few
  a feature engineering wrapper for sklearn
  ☆52Updated 5 years ago
• ili3p / HORD
  Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
  ☆115Updated 8 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆183Updated 6 years ago
• caioaao / wolpert
  A stacked generalization framework. Built on top of scikit learn
  ☆57Updated 2 years ago
• vruvora / reinforcement-learning-kdd
  ☆42Updated 7 years ago
• levyben / DeepSuperLearner
  DeepSuperLearner - Python implementation of the deep ensemble algorithm
  ☆135Updated 7 years ago
• seba-1511 / randopt
  Streamlined machine learning experiment management.
  ☆107Updated 5 years ago
• suriyadeepan / BayesianML
  Experiments in Bayesian Machine Learning
  ☆69Updated 6 years ago
• genixpro / hypermax
  Better, faster hyper-parameter optimization
  ☆113Updated last year
• hyperopt / hyperopt-nnet
  Hyperparameter optimization for neural networks
  ☆48Updated 11 years ago
• abhishekmalali / TimeFlow
  Tensorflow for Time Series Applications
  ☆68Updated 7 years ago
• EpistasisLab / scikit-mdr
  A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
  ☆125Updated 3 months ago
• sigopt / sigopt-sklearn
  SigOpt wrappers for scikit-learn methods
  ☆75Updated 2 years ago
• vene / pyowl
  Ordered Weighted L1 regularization for classification and regression in Python
  ☆52Updated 7 years ago
• automl / pysmac
  simple python interface to SMAC.
  ☆21Updated 7 years ago
• EvoML / EvoML
  Using Genetic Algorithms to aid Machine Learning
  ☆19Updated 7 years ago
• udellgroup / oboe
  An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.
  ☆84Updated 3 years ago
• johannespetrat / OptML
  Implementation of several black-box optimisation methods to tune hyperparameters of machine learning models.
  ☆77Updated 7 years ago
• ofirnachum / uncertainty_gbm
  Sklearn implementation of GBM to predict mu(X) and std(X) on heteroscedastic data
  ☆26Updated 9 years ago
• 0011001011 / vizuka
  Explore high-dimensional datasets and how your algo handles specific regions.
  ☆107Updated 7 years ago
• NICTA / revrand
  A library of scalable Bayesian generalised linear models with fancy features
  ☆60Updated 8 years ago
• hamaadshah / gan_tensorflow
  Automatic feature engineering using Generative Adversarial Networks using TensorFlow.
  ☆51Updated 2 years ago
• mpearmain / gestalt
  A helper library for data science pipeline
  ☆36Updated 6 years ago
• predict-idlab / GENESIM
  [DEPRECATED] An innovative technique that constructs an ensemble of decision trees and converts this ensemble into a single, interpretab…
  ☆79Updated 4 years ago
• ogrisel / pygbm
  Experimental Gradient Boosting Machines in Python with numba.
  ☆185Updated 6 years ago
• sigopt / sigopt-python
  Simple Python interface for the SigOpt API
  ☆71Updated last month
• cgnorthcutt / rankpruning
  🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.
  ☆83Updated 3 years ago
• LucaAmbrogioni / GP-CaKe-project
  Bayesian Effective Connectivity
  ☆54Updated 6 years ago
• abhishekkrthakur / automl_gpu
  ☆25Updated 9 years ago