csinva / imodelsLinks
Interpretable ML package π for concise, transparent, and accurate predictive modeling (sklearn-compatible).
β1,491Updated 2 weeks ago
Alternatives and similar repositories for imodels
Users that are interested in imodels are comparing it to the libraries listed below
Sorting:
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.β1,454Updated this week
- Generate Diverse Counterfactual Explanations for any machine learning model.β1,443Updated last month
- Extra blocks for scikit-learn pipelines.β1,354Updated 2 months ago
- Fast SHAP value computation for interpreting tree-based modelsβ541Updated 2 years ago
- Feature engineering package with sklearn like functionalityβ2,125Updated this week
- Machine learning with dataframesβ1,452Updated last week
- Predictive Power Score (PPS) in Pythonβ1,156Updated 8 months ago
- Leave One Feature Out Importanceβ836Updated 6 months ago
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.β1,993Updated 3 months ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.β579Updated last year
- Algorithms for explaining machine learning modelsβ2,551Updated last week
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.β631Updated last year
- moDel Agnostic Language for Exploration and eXplanationβ1,439Updated last month
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadβ¦β663Updated 6 months ago
- EvalML is an AutoML library written in python.β826Updated this week
- Natural Gradient Boosting for Probabilistic Predictionβ1,771Updated this week
- A Python library that helps data scientists to infer causation rather than observing correlation.β2,367Updated last year
- machine learning with logical rules in Pythonβ644Updated last year
- A Python package for modular causal inference analysis and model evaluationsβ786Updated 5 months ago
- A drop-in replacement for Scikit-Learnβs GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.β468Updated last year
- π Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Modelsβ2,947Updated last month
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.β644Updated 7 months ago
- A Python package for causal inference in quasi-experimental settingsβ1,034Updated last week
- The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to sβ¦β703Updated last week
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.β602Updated 9 months ago
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.β2,442Updated last month
- Human-explainable AI.β525Updated last week
- python partial dependence plot toolboxβ861Updated last year
- Multiple Imputation with LightGBM in Pythonβ390Updated last year
- Natural Intelligence is still a pretty good idea.β820Updated last year