Alternatives and similar repositories for treeFarms

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

• soda-inria / hazardous
  Competing Risks and Survival Analysis
  ☆113Updated 3 months ago
• interpretml / gam-changer
  Editing machine learning models to reflect human knowledge and values
  ☆128Updated 2 years ago
• Yu-Group / veridical-flow
  Making it easier to build stable, trustworthy data-science pipelines based on the PCS framework.
  ☆72Updated last year
• neurodata / treeple
  Scikit-learn compatible decision trees beyond those offered in scikit-learn
  ☆85Updated 2 weeks ago
• almost-matching-exactly / DAME-FLAME-Python-Package
  A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data
  ☆62Updated 5 months ago
• scikit-learn-contrib / skglm
  Fast and modular sklearn replacement for generalized linear models
  ☆187Updated 3 months ago
• soda-inria / carte
  Repository for CARTE: Context-Aware Representation of Table Entries
  ☆161Updated 4 months ago
• wilsonjr / ClusterShapley
  Explaining dimensionality results using SHAP values
  ☆55Updated this week
• RianneSchouten / pyampute
  Missing data amputation and exploration functions for Python
  ☆72Updated 3 years ago
• givasile / effector
  Effector - a Python package for global and regional effect methods
  ☆117Updated last month
• corels / pycorels
  Public home of pycorels, the python binding to CORELS
  ☆80Updated 5 years ago
• sherbold / autorank
  ☆86Updated 6 months ago
• py-why / pywhy-stats
  Python package for (conditional) independence testing and statistical functions related to causality.
  ☆29Updated last week
• salimamoukou / acv00
  ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…
  ☆102Updated 3 years ago
• andreArtelt / ceml
  CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
  ☆46Updated 7 months ago
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆282Updated 2 weeks ago
• meeliskull / prg
  Software to create Precision-Recall-Gain curves and calculate area under the curve
  ☆42Updated 3 years ago
• aangelopoulos / ppi_py
  A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
  ☆272Updated 4 months ago
• max-little / GRAPL
  GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
  ☆83Updated last year
• flemmerich / pysubgroup
  ☆72Updated 2 months ago
• interpretml / fastSparse
  ☆24Updated 2 years ago
• scikit-learn-contrib / scikit-dimension
  A Python package for intrinsic dimension estimation
  ☆95Updated 3 months ago
• py-why / pywhy-graphs
  [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.
  ☆62Updated 3 weeks ago
• hyungkwonko / umato
  Uniform Manifold Approximation with Two-phase Optimization (IEEE VIS 2022 short)
  ☆114Updated 4 months ago
• scikit-activeml / scikit-activeml
  scikit-activeml: A Comprehensive and User-friendly Active Learning Library
  ☆181Updated last week
• y0-causal-inference / y0
  ❓y0 (pronounced "why not?") is for causal inference in Python
  ☆66Updated this week
• causalvis / causalvis
  ☆47Updated last year
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆75Updated last year
• Jimmy-Lin / GeneralizedOptimalSparseDecisionTrees
  Generalized Optimal Sparse Decision Trees
  ☆70Updated last year
• MLResearchAtOSRAM / cause2e
  The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).
  ☆63Updated 8 months ago