Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses
Fuzzy machine learning algorithms implementing the scikit-learn interface.
Extends scikit-learn with new models, transformers, metrics, plotting.
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
Utilities for easy use of custom losses in CatBoost, LightGBM, XGBoost.
Implementations of the machine learning algorithm with Python and numpy
Some fundamental machine learning and data-analysis techniques are explained through realistic ex...
An experiment about re-implementing supervised learning models based on shallow neural network ap...
Oblique Tree classifier based on SVM nodes
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-co...
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large languag...
Conformal classifiers, regressors and predictive systems
Machine Learning with a Reject Option
A scikit-learn-compatible module for estimating prediction intervals.
Utilities for scikit-learn. Append prediction to x, append prediction to x single, append x predi...
Scikit-learn compatible estimation of general graphical models