sibirbil / RuleDiscovery
Two algorithms based on linear programming to discover classification rules for interpretable learning.
☆21Updated last week
Related projects ⓘ
Alternatives and complementary repositories for RuleDiscovery
- Optimization-Based Rule Learning for Classification☆40Updated last week
- Materials for conference talks and workshops☆29Updated 10 months ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆88Updated 10 months ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆100Updated 2 years ago
- Learning with Subset Stacking☆22Updated 2 years ago
- Repository for the explanation method Calibrated Explanations (CE)☆54Updated this week
- Causality-Aware Local Interpretable Model Agnostic Explanations☆11Updated 2 months ago
- A presention of core concepts and a data generator making easier using tabular data with TensorFlow and Keras☆41Updated last year
- CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system☆76Updated last year
- Code used to obtain results for my medium articles☆70Updated last year
- ☆48Updated last year
- A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES☆31Updated 9 months ago
- Introduction to GIS & Remote Sensing materials.☆16Updated 3 years ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆128Updated 3 months ago
- Rule covering for interpretation and boosting☆17Updated 3 years ago
- Evaluate real and synthetic datasets against each other☆80Updated last month
- ALE Plots with python☆59Updated 7 months ago
- Anadolu Hayat Emeklilik Datathon - Coderspace☆18Updated 2 years ago
- Tutorial on how to use the SHAP library to explain the feature importance with Shapley values.☆19Updated 5 years ago
- ☆48Updated last year
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆160Updated 2 years ago
- Nested cross-validation for unbiased predictions. Can be used with Scikit-Learn, XGBoost, Keras and LightGBM, or any other estimator that…☆62Updated 5 years ago
- An open-source unsupervised time-series anomaly detection package by Getcontact Data Team☆44Updated 2 years ago
- ☆11Updated 7 months ago
- Arguably the best missing values imputation method.☆57Updated 2 months ago
- TimeSHAP explains Recurrent Neural Network predictions.☆162Updated 11 months ago
- Fast implementation of Venn-ABERS probabilistic predictors☆71Updated 9 months ago
- ☆18Updated 6 months ago
- Experimental library integrating LLM capabilities to support causal analyses☆86Updated 2 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆42Updated last year