Alternatives and similar repositories for mlens:

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

• hyperopt / hyperopt-sklearn
  Hyper-parameter optimization for sklearn
  ☆1,621Updated 3 weeks ago
• scikit-learn-contrib / boruta_py
  Python implementations of the Boruta all-relevant feature selection method.
  ☆1,561Updated 8 months ago
• SauceCat / PDPbox
  python partial dependence plot toolbox
  ☆855Updated 7 months ago
• vecxoz / vecstack
  Python package for stacking (machine learning technique)
  ☆691Updated 8 months ago
• scikit-learn-contrib / skope-rules
  machine learning with logical rules in Python
  ☆633Updated last year
• limexp / xgbfir
  XGBoost Feature Interactions Reshaped
  ☆427Updated 7 years ago
• scikit-learn-contrib / DESlib
  A Python library for dynamic classifier and ensemble selection
  ☆484Updated last year
• EpistasisLab / scikit-rebate
  A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
  ☆416Updated 2 years ago
• RGF-team / rgf
  Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…
  ☆381Updated 3 years ago
• abhayspawar / featexp
  Feature exploration for supervised learning
  ☆763Updated 4 years ago
• christophM / rulefit
  Python implementation of the rulefit algorithm
  ☆420Updated last year
• rsteca / sklearn-deap
  Use evolutionary algorithms instead of gridsearch in scikit-learn
  ☆773Updated last year
• scikit-learn-contrib / scikit-learn-contrib
  scikit-learn compatible projects
  ☆410Updated last week
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆513Updated 3 weeks ago
• andosa / treeinterpreter
  ☆757Updated last year
• chasedehan / BoostARoota
  A fast xgboost feature selection algorithm
  ☆221Updated 4 years ago
• rushter / heamy
  A set of useful tools for competitive data science.
  ☆550Updated 2 years ago
• TeamHG-Memex / eli5
  A library for debugging/inspecting machine learning classifiers and explaining their predictions
  ☆2,770Updated 2 years ago
• MaxHalford / xam
  Personal data science and machine learning toolbox
  ☆365Updated 5 years ago
• HunterMcGushion / hyperparameter_hunter
  Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
  ☆705Updated 4 years ago
• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆799Updated 2 years ago
• scikit-learn-contrib / stability-selection
  scikit-learn compatible implementation of stability selection.
  ☆212Updated last year
• parrt / random-forest-importances
  Code to compute permutation and drop-column importances in Python scikit-learn models
  ☆610Updated 3 weeks ago
• h2oai / pystacknet
  ☆288Updated 2 years ago
• stanfordmlgroup / ngboost
  Natural Gradient Boosting for Probabilistic Prediction
  ☆1,694Updated last week
• jphall663 / interpretable_machine_learning_with_python
  Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …
  ☆676Updated 9 months ago
• dmbee / seglearn
  Python module for machine learning time series:
  ☆574Updated 2 years ago
• WillKoehrsen / hyperparameter-optimization
  Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
  ☆628Updated last year
• h2oai / mli-resources
  H2O.ai Machine Learning Interpretability Resources
  ☆488Updated 4 years ago
• alteryx / Automated-Manual-Comparison
  Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.
  ☆327Updated 4 years ago