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
☆52Updated 2 months ago
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☆265Updated 2 months ago
- Python implementation of binary and multi-class Venn-ABERS calibration☆191Updated 3 weeks ago
- Practical Guide to Applied Conformal Prediction, published by Packt☆192Updated last month
- Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.☆224Updated last year
- Forecasting: principles and practice in python☆191Updated 2 years ago
- The Orange Book of Machine Learning☆49Updated last month
- This projects contains different conformal methods and approaches. Includes code generated for a experimental evaluation of a multidimens…☆19Updated last year
- Repository for the explanation method Calibrated Explanations (CE)☆70Updated this week
- Quantile Regression Forests compatible with scikit-learn.☆243Updated 2 weeks ago
- WarpGBM: High-Speed Gradient Boosting☆93Updated this week
- Forecasting: Principles and Practice☆61Updated 4 years ago
- Integrated tool for model development and validation☆31Updated last month
- ☆289Updated 2 years ago
- Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.☆26Updated 8 months ago
- Compendium of free ML reading resources☆417Updated last month
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆114Updated 3 weeks ago
- Shapley Interactions and Shapley Values for Machine Learning☆622Updated this week
- The best repo showing why bayesianism is a complete misnomer☆31Updated last month
- Python package for conformal prediction☆537Updated 3 weeks ago
- ☆33Updated last year
- Repository for the book Machine Learning Learning Beyond Point Predictions: Uncertainty Quantification, by Rafael Izbicki.☆32Updated 3 months ago
- ☆115Updated last year
- Multi-class probabilistic classification using inductive and cross Venn–Abers predictors☆49Updated 3 years ago
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆154Updated last week
- ☆201Updated last week
- A Library for Conformal Hyperparameter Tuning☆101Updated 3 weeks ago
- 👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.☆350Updated 4 months ago
- Here are the notebooks for the Gaussian Processes and Bayesian Optimization course. The notebooks can be executed in Google Colab.☆27Updated last year
- Fast implementation of Venn-ABERS probabilistic predictors☆75Updated last year
- Fast, high-quality forecasts on relational and multivariate time-series data powered by new feature learning algorithms and automated ML.☆228Updated last week