csinva / imodels
Interpretable ML package π for concise, transparent, and accurate predictive modeling (sklearn-compatible).
β1,400Updated 2 weeks ago
Related projects β
Alternatives and complementary repositories for imodels
- A scikit-learn-compatible module to estimate prediction intervals and control risks based on conformal predictions.β1,302Updated this week
- Extra blocks for scikit-learn pipelines.β1,278Updated this week
- Generate Diverse Counterfactual Explanations for any machine learning model.β1,365Updated 7 months ago
- Fast SHAP value computation for interpreting tree-based modelsβ522Updated last year
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.β589Updated 9 months ago
- Prepping tables for machine learningβ1,218Updated this week
- Feature engineering package with sklearn like functionalityβ1,927Updated last week
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.β567Updated 5 months ago
- python partial dependence plot toolboxβ845Updated 2 months ago
- Algorithms for explaining machine learning modelsβ2,414Updated this week
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadβ¦β591Updated 6 months ago
- Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.β1,222Updated 3 weeks ago
- The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to sβ¦β688Updated 2 weeks ago
- Natural Gradient Boosting for Probabilistic Predictionβ1,655Updated 3 weeks ago
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.β2,312Updated 4 months ago
- A standard framework for modelling Deep Learning Models for tabular dataβ1,382Updated this week
- A drop-in replacement for Scikit-Learnβs GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.β467Updated last year
- moDel Agnostic Language for Exploration and eXplanationβ1,375Updated last month
- Leave One Feature Out Importanceβ818Updated 10 months ago
- OmniXAI: A Library for eXplainable AIβ876Updated 3 months ago
- A Python package for causal inference in quasi-experimental settingsβ914Updated this week
- Python implementation of the rulefit algorithmβ411Updated last year
- An extension of XGBoost to probabilistic modellingβ563Updated 4 months ago
- A Python package for modular causal inference analysis and model evaluationsβ735Updated 3 months ago
- Algorithms for outlier, adversarial and drift detectionβ2,249Updated this week
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.β1,884Updated 4 months ago
- machine learning with logical rules in Pythonβ625Updated 9 months ago
- Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Infβ¦β480Updated 3 weeks ago
- Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explβ¦β457Updated 3 weeks ago
- Natural Intelligence is still a pretty good idea.β797Updated 4 months ago