ealcobaca / meta-padawan
Meta-Padawan solution to the NeurIPS (2021) - Few-shot learning competition.
☆9Updated 3 years ago
Alternatives and similar repositories for meta-padawan:
Users that are interested in meta-padawan are comparing it to the libraries listed below
- R package for data complexity measures for imbalanced classification tasks☆9Updated 3 years ago
- Meaningful Local Explanation for Machine Learning Models☆40Updated last year
- Python Meta-Feature Extractor package.☆131Updated 8 months ago
- Post-hoc Nemenyi test for algorithm statistical comparison.☆21Updated 4 years ago
- Extended Complexity Library in R☆57Updated 4 years ago
- Data structures' lectures for Computer Engineering course, UTFPR - Apucarana☆32Updated 2 years ago
- Meta-Feature Extractor☆28Updated 2 years ago
- An image meta-feature extractor for meta-learning tasks.☆12Updated last year
- ☆15Updated 6 years ago
- An automated machine learning tool aimed to facilitate AutoML research.☆96Updated 6 months ago
- Random Forest with Dynamic Tree Selection Monte Carlo Based (RF-TSMC).☆48Updated 3 months ago
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆160Updated 2 years ago
- Fast implementation of Venn-ABERS probabilistic predictors☆72Updated last year
- Dataset shift diagnostics in Python☆34Updated last year
- Python implementation of binary and multi-class Venn-ABERS calibration☆145Updated 6 months ago
- Extra functionalities for river☆14Updated 9 months ago
- A power-full Shapley feature selection method.☆203Updated 10 months ago
- An unsupervised feature selection technique using supervised algorithms such as XGBoost☆89Updated last year
- Machine Learning solutions for Kaggle contests☆15Updated 4 years ago
- All Relevant Feature Selection☆131Updated last month
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆99Updated 2 years ago
- Python package for Imputation Methods☆247Updated last year
- Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.☆134Updated last month
- An extension of CatBoost to probabilistic modelling☆142Updated last year
- A Python package for building Bayesian models with TensorFlow or PyTorch☆173Updated 2 years ago
- Feature selection package based on SHAP and target permutation, for pandas and Spark☆30Updated 3 years ago
- Local Universal Rule-based Explanations☆12Updated last month
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆572Updated 9 months ago
- For calculating global feature importance using Shapley values.☆266Updated this week
- Improving XGBoost survival analysis with embeddings and debiased estimators☆327Updated 5 months ago