younader / dnnr
The Python package of differential nearest neighbors regression (DNNR): Raising KNN-regression to levels of gradient boosting method. Build on-top of Numpy, Scikit-Learn, and Annoy.
☆16Updated 2 years ago
Alternatives and similar repositories for dnnr:
Users that are interested in dnnr are comparing it to the libraries listed below
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 4 years ago
- A repo for transfer learning with deep tabular models☆101Updated last year
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆60Updated 4 years ago
- Influence Estimation for Gradient-Boosted Decision Trees☆26Updated 8 months ago
- A lightweight implementation of removal-based explanations for ML models.☆57Updated 3 years ago
- TabDPT: Scaling Tabular Foundation Models☆24Updated last week
- An Empirical Framework for Domain Generalization In Clinical Settings☆29Updated 2 years ago
- A benchmark for distribution shift in tabular data☆49Updated 7 months ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- Tools for training explainable models using attribution priors.☆120Updated 3 years ago
- Neural Additive Models (Google Research)☆69Updated 3 years ago
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated 2 years ago
- ☆35Updated last year
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)☆21Updated last year
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated 8 months ago
- ☆124Updated 3 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆130Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- ☆90Updated last year
- Adaptive and Reliable Classification: efficient conformity scores for multi-class classification problems☆31Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 8 months ago
- Beta calibration☆27Updated 11 months ago
- Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)☆106Updated 2 years ago
- ☆29Updated last year
- For calculating Shapley values via linear regression.☆66Updated 3 years ago
- Local explanations with uncertainty 💐!☆39Updated last year
- Detecting Statistical Interactions from Neural Network Weights☆47Updated 4 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆43Updated 2 years ago