Alternatives and similar repositories for imbalanced-learn:

Users that are interested in imbalanced-learn are comparing it to the libraries listed below

• hyperopt / hyperopt
  Distributed Asynchronous Hyperparameter Optimization in Python
  ☆7,402Updated 3 months ago
• TeamHG-Memex / eli5
  A library for debugging/inspecting machine learning classifiers and explaining their predictions
  ☆2,769Updated 2 weeks ago
• rasbt / mlxtend
  A library of extension and helper modules for Python's data analysis and machine learning libraries.
  ☆4,996Updated 3 months ago
• automl / auto-sklearn
  Automated Machine Learning with scikit-learn
  ☆7,818Updated 3 months ago
• scikit-optimize / scikit-optimize
  Sequential model-based optimization with a `scipy.optimize` interface
  ☆2,770Updated last year
• skorch-dev / skorch
  A scikit-learn compatible neural network library that wraps PyTorch
  ☆6,014Updated last week
• reiinakano / scikit-plot
  An intuitive library to add plotting functionality to scikit-learn objects.
  ☆2,433Updated 8 months ago
• alteryx / featuretools
  An open source python library for automated feature engineering
  ☆7,431Updated 2 weeks ago
• scikit-learn-contrib / category_encoders
  A library of sklearn compatible categorical variable encoders
  ☆2,443Updated last month
• DistrictDataLabs / yellowbrick
  Visual analysis and diagnostic tools to facilitate machine learning model selection.
  ☆4,339Updated 2 months ago
• marcotcr / lime
  Lime: Explaining the predictions of any machine learning classifier
  ☆11,862Updated 9 months ago
• dmlc / xgboost
  Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on sing…
  ☆26,875Updated this week
• maxpumperla / hyperas
  Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
  ☆2,179Updated 2 years ago
• interpretml / interpret
  Fit interpretable models. Explain blackbox machine learning.
  ☆6,476Updated last week
• hyperopt / hyperopt-sklearn
  Hyper-parameter optimization for sklearn
  ☆1,622Updated 2 weeks ago
• microsoft / LightGBM
  A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used …
  ☆17,167Updated last week
• bayesian-optimization / BayesianOptimization
  A Python implementation of global optimization with gaussian processes.
  ☆8,209Updated last week
• EpistasisLab / tpot
  A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
  ☆9,892Updated 2 months ago
• benhamner / Metrics
  Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave
  ☆1,637Updated 2 years ago
• jmschrei / pomegranate
  Fast, flexible and easy to use probabilistic modelling in Python.
  ☆3,436Updated 2 months ago
• scikit-learn-contrib / sklearn-pandas
  Pandas integration with sklearn
  ☆2,828Updated last year
• pyro-ppl / pyro
  Deep universal probabilistic programming with Python and PyTorch
  ☆8,742Updated last week
• IDSIA / sacred
  Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
  ☆4,297Updated 5 months ago
• scikit-learn-contrib / boruta_py
  Python implementations of the Boruta all-relevant feature selection method.
  ☆1,565Updated 8 months ago
• blei-lab / edward
  A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
  ☆4,840Updated last year
• MLWave / Kaggle-Ensemble-Guide
  Code for the Kaggle Ensembling Guide Article on MLWave
  ☆1,579Updated 7 years ago
• statsmodels / statsmodels
  Statsmodels: statistical modeling and econometrics in Python
  ☆10,620Updated last week
• blue-yonder / tsfresh
  Automatic extraction of relevant features from time series:
  ☆8,736Updated 2 months ago
• snorkel-team / snorkel
  A system for quickly generating training data with weak supervision
  ☆5,854Updated last year
• HIPS / autograd
  Efficiently computes derivatives of NumPy code.
  ☆7,254Updated this week