Alternatives and similar repositories for rule_estimator:

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

• ag-ds-bubble / tseuler
  A library for Time-Series exploration, analysis & modelling.
  ☆17Updated 4 years ago
• fugue-project / tune
  An abstraction layer for parameter tuning
  ☆35Updated 6 months ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆51Updated last year
• koaning / scikit-prune
  Prune your sklearn models
  ☆19Updated 4 months ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 3 years ago
• formlio / forml
  ForML - A development framework and MLOps platform for the lifecycle management of data science projects
  ☆104Updated last year
• smazzanti / valicast
  Validation for forecasts
  ☆18Updated 2 years ago
• koaning / scikit-partial
  Pipeline components that support partial_fit.
  ☆45Updated 7 months ago
• sktime / sktime-tutorial-pydata-global-2022
  sktime - python toolbox for time series: pipelines and transformers
  ☆25Updated 2 years ago
• sktime / sktime-tutorial-pydata-berlin-2022
  ☆39Updated 2 years ago
• petersontylerd / mlmachine
  mlmachine accelerates machine learning experimentation
  ☆30Updated 3 years ago
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆25Updated 2 years ago
• fastforwardlabs / structural-time-series
  Structural Time Series on US electricity demand data
  ☆22Updated 4 years ago
• unravelin / code-test-data-science
  Data Scientist code test
  ☆19Updated 4 years ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• ahmed-mohamed-sn / ATgfe
  Automated Transparent Genetic Feature Engineering
  ☆22Updated last year
• AutoViML / lazytransform
  Automatically transform all categorical, date-time, NLP variables to numeric in a single line of code for any data set any size.
  ☆64Updated last month
• tlentali / leab
  📈🔍 Lets Python do AB testing analysis
  ☆76Updated 10 months ago
• Spratiher9 / Sparkora
  Powerful rapid automatic EDA and feature engineering library with a very easy to use API 🌟
  ☆53Updated 3 years ago
• gdmarmerola / cfml_tools
  My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable an…
  ☆29Updated 2 years ago
• dataiku / dss-plugin-model-drift
  Model drift detection
  ☆11Updated last year
• lorentzenchr / model-diagnostics
  Tools for diagnostics and assessment of (machine learning) models
  ☆34Updated last week
• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆52Updated 6 months ago
• MaxHalford / naked
  The simplest way to deploy a machine learning model
  ☆23Updated 2 years ago
• guillermo-navas-palencia / cprior
  Fast Bayesian A/B and Multivariate testing.
  ☆36Updated 2 years ago
• tonyleidong / OptimalFlow
  OptimalFlow is an omni-ensemble and scalable automated machine learning Python toolkit, which uses Pipeline Cluster Traversal Experiments…
  ☆27Updated last year
• NITRO-AI / NitroFE
  NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for …
  ☆106Updated 2 years ago
• jphall663 / hc_ml
  Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
  ☆22Updated 5 years ago
• MaartenGr / UnitTesting
  Guide for applying Unit Testing in data-driven projects
  ☆19Updated 4 years ago
• zelros / cinnamon
  CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
  ☆77Updated 2 years ago