ottenbreit-data-science / aplrLinks
APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.
☆21Updated 3 months ago
Alternatives and similar repositories for aplr
Users that are interested in aplr are comparing it to the libraries listed below
Sorting:
- Repository for the explanation method Calibrated Explanations (CE)☆69Updated 2 months ago
- ☆22Updated last year
- Generalized additive model with pairwise interactions☆66Updated last year
- (ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles☆92Updated last month
- Adaptive Conformal Prediction Intervals (ACPI) is a Python package that enhances the Predictive Intervals provided by the split conformal…☆29Updated 2 years ago
- Python implementation of adversarial random forests for density estimation and generative modelling☆31Updated last year
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆102Updated 2 years ago
- Contains the code to run the different models considered in the paper "Valid prediction intervals for regression problems"☆19Updated 2 years ago
- Repository for TabICL: A Tabular Foundation Model for In-Context Learning on Large Data☆150Updated 3 weeks ago
- Effector - a Python package for global and regional effect methods☆113Updated 2 weeks ago
- Fast implementation of Venn-ABERS probabilistic predictors☆73Updated last year
- Bayesian time series forecasting and decision analysis☆116Updated 2 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 3 years ago
- A Library for Conformal Hyperparameter Tuning☆31Updated last week
- Probabilistic prediction with XGBoost.☆111Updated 4 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- Arguably the best missing values imputation method.☆69Updated 7 months ago
- For calculating global feature importance using Shapley values.☆272Updated last week
- Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost☆34Updated 8 months ago
- GAMI-Net: Generalized Additive Models with Structured Interactions☆31Updated 3 years ago
- A Living Benchmark for Machine Learning on Tabular Data☆105Updated last week
- SSCP: Improving Adaptive Conformal Prediction Using Self-supervised Learning (AISTATS 2023)☆17Updated 2 years ago
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆48Updated 3 years ago
- An extension of Py-Boost to probabilistic modelling☆23Updated 2 years ago
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆110Updated 3 months ago
- Tabular In-Context Learning☆82Updated 5 months ago
- ☆39Updated 7 months ago
- Quantile Regression Forests compatible with scikit-learn.☆235Updated this week
- TimeSHAP explains Recurrent Neural Network predictions.☆180Updated last year
- Repository for CARTE: Context-Aware Representation of Table Entries☆139Updated 4 months ago