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 last week
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)☆70Updated this week
- (ICLR 2024) GRANDE: Gradient-Based Decision Tree Ensembles☆93Updated 3 months ago
- Contains the code to run the different models considered in the paper "Valid prediction intervals for regression problems"☆20Updated 2 years ago
- Effector - a Python package for global and regional effect methods☆116Updated 2 months ago
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆49Updated 3 years ago
- ☆22Updated last year
- An extension of Py-Boost to probabilistic modelling☆24Updated 2 years ago
- ☆40Updated 9 months ago
- Fast implementation of Venn-ABERS probabilistic predictors☆75Updated last year
- Bayesian time series forecasting and decision analysis☆117Updated 2 years ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- Generalized additive model with pairwise interactions☆66Updated last year
- 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
- Inference code for "TabDPT: Scaling Tabular Foundation Models on Real Data"☆59Updated last week
- Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion …☆49Updated 3 weeks ago
- 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
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆114Updated last week
- For calculating global feature importance using Shapley values.☆276Updated last week
- A Python Package for Probabilistic Prediction☆22Updated 4 years ago
- Scikit-learn compatible decision trees beyond those offered in scikit-learn☆85Updated last week
- Conformal Anomaly Detection☆49Updated this week
- A short introduction to Conformal Prediction methods, with a few examples for classification and regression from the Astrophysical domain…☆12Updated last year
- Fast and incremental explanations for online machine learning models. Works best with the river framework.☆55Updated 9 months ago
- Multiple quantiles estimation model maintaining non-crossing condition (or monotone quantile condition) using LightGBM and XGBoost☆36Updated 10 months ago
- Ensemble wavelet based neural network for generating epidemiological forecasting (epicasting)☆15Updated 3 weeks ago
- Official code for: Conformal prediction interval for dynamic time-series (conference, ICML 21 Long Presentation) AND Conformal prediction…☆122Updated last year
- A framework for calibration measurement of binary probabilistic models☆29Updated last year
- Lightweight Python package for generating classification intervals in binary classification tasks using Pearson residuals and conformal p…☆22Updated 4 months ago
- A Library for Conformal Hyperparameter Tuning☆99Updated last week