Alternatives and similar repositories for mimic

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

• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• ralphhaygood / sklearn-gbmi
  scikit-learn gradient-boosting-model interactions
  ☆25Updated 2 years ago
• lopusz / pydata-berlin-2018
  ☆15Updated 6 years ago
• petersontylerd / mlmachine
  mlmachine accelerates machine learning experimentation
  ☆30Updated 3 years ago
• rafaelvalle / MDI
  Missing Data Imputation Python Library
  ☆35Updated 5 years ago
• alteryx / categorical_encoding
  Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library
  ☆51Updated 2 years ago
• capitalone / global-attribution-mapping
  GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations
  ☆34Updated 2 months ago
• navdeep-G / interpretable-ml
  Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
  ☆21Updated 3 years ago
• MI2DataLab / pyBreakDown
  Python implementation of R package breakDown
  ☆43Updated last year
• stanfordmlgroup / risk-adjustment-ml
  Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.
  ☆12Updated 5 years ago
• mthorrell / wideboost
  Wrappers to implement wide boosting using popular boosting frameworks
  ☆13Updated 2 years ago
• mcasl / PipeGraph
  Home of the PipeGraph extension to Scikit-Learn
  ☆24Updated 3 months ago
• donlnz / morfist
  Multi-target Random Forest implementation that can mix both classification and regression tasks
  ☆26Updated 5 years ago
• dbenielli / scikit-multimodallearn
  This Python package implements algorithms for multiviews (multimodals) learning
  ☆14Updated 8 months ago
• saket-maheshwary / AutoLearn
  AutoLearn, a domain independent regression-based feature learning algorithm.
  ☆30Updated 5 years ago
• ShopRunner1 / octopod
  Train multi-task image, text, or ensemble (image + text) models
  ☆45Updated last year
• MaxHalford / starboost
  Gradient boosting on steroids
  ☆28Updated last year
• MaxHalford / naked
  The simplest way to deploy a machine learning model
  ☆23Updated 2 years ago
• drivendataorg / rinse-over-run
  Winners of the Sustainable Industry: Rinse Over Run competition
  ☆21Updated last year
• tblume1992 / BetaBoost
  A small wrapper to do Beta Boosting with XgBoost
  ☆15Updated 3 years ago
• thuijskens / scikit-hyperband
  A scikit-learn compatible implementation of hyperband
  ☆76Updated 5 years ago
• Brett-Kennedy / CountsOutlierDetector
  Interpretable, intuitive outlier detector intended for categorical and numeric data.
  ☆10Updated last year
• shaypal5 / stationarizer
  Smart, automatic detection and stationarization of non-stationary time series data.
  ☆29Updated 2 years ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆51Updated last year
• AnotherSamWilson / fastshap
  Batch shap calculations.
  ☆31Updated 2 years ago
• anonICLR2020 / node
  ☆26Updated 5 years ago
• tonyduan / hte-prediction-rcts
  Predicting treatment effects from RCTs (Circulation: CQO 2019).
  ☆10Updated 3 years ago
• Didayolo / autopandas
  Process, visualize and use data easily.
  ☆20Updated last year
• jphall663 / responsible_xai
  Guidelines for the responsible use of explainable AI and machine learning.
  ☆17Updated 2 years ago
• chlubba / op_importance
  Compute set of important operations for HCTSA code
  ☆26Updated 5 years ago