valeman / smote_is_what_you_dont_needLinks
The best repository showing why SMOTE and resampling methods might not be the answer for imbalanced data problems
☆51Updated last month
Alternatives and similar repositories for smote_is_what_you_dont_need
Users that are interested in smote_is_what_you_dont_need are comparing it to the libraries listed below
Sorting:
- The repository to showcase the best framework for tabular data - the Awesome CatBoost☆264Updated last month
- Python implementation of binary and multi-class Venn-ABERS calibration☆189Updated this week
- Practical Guide to Applied Conformal Prediction, published by Packt☆190Updated last week
- Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.☆223Updated last year
- Repository for the explanation method Calibrated Explanations (CE)☆70Updated this week
- Python package for conformal prediction☆517Updated 2 months ago
- The Orange Book of Machine Learning☆49Updated 2 weeks ago
- Forecasting: principles and practice in python☆185Updated 2 years ago
- Quantile Regression Forests compatible with scikit-learn.☆241Updated last week
- Integrated tool for model development and validation☆31Updated last month
- This projects contains different conformal methods and approaches. Includes code generated for a experimental evaluation of a multidimens…☆19Updated last year
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆112Updated 4 months ago
- Shapley Interactions and Shapley Values for Machine Learning☆612Updated this week
- WarpGBM: High-Speed Gradient Boosting☆91Updated 2 months ago
- ☆287Updated 2 years ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆145Updated 2 weeks ago
- Fast implementation of Venn-ABERS probabilistic predictors☆75Updated last year
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆49Updated 3 years ago
- Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.☆26Updated 7 months ago
- Compendium of free ML reading resources☆396Updated 2 weeks ago
- Forecasting: Principles and Practice☆61Updated 4 years ago
- ☆115Updated last year
- ☆33Updated last year
- 👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.☆346Updated 3 months ago
- ☆202Updated 2 weeks ago
- A resource list for causality in statistics, data science and physics☆265Updated last month
- A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.☆45Updated last month
- ☆49Updated 9 months ago
- Feature engineering package with sklearn like functionality☆56Updated last year
- A framework for calibration measurement of binary probabilistic models☆28Updated last year