Stars
A scalable linear programming based algorithm for K-Means clustering
Codebase for reproducing the experiments of the semantic uncertainty paper (short-phrase and sentence-length experiments).
Riskomon is an interactive visualization tool for the exploration of a Rashomon set of scoring system models—that is, a collection of equally-good risk score models—obtained from the FasterRisk alg…
Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
Code repository for the manuscript: 'Assessing performance in prediction models with survival outcomes: practical guidance for Cox proportional hazards models' (published in Annals of Internal Medi…
Survival analysis in health economic evaluation Contains a suite of functions to systematise the workflow involving survival analysis in health economic evaluation. survHE can fit a large range of …
🔮 Benchmarking and visualization toolkit for penalized Cox models
Piece-wise exponential Additive Mixed Modeling tools
A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can …
Datasets for Predictive Maintenance
Data loader for most common datasets in survival analysis.
Survival analysis built on top of scikit-learn
DISCS: The code base for the Benchmark for Discrete Sampling
A Low-Rank ADMM Splitting Approach for Semidefinite Programming
Awesome machine learning for combinatorial optimization papers.
Code supplement to paper "Sparse PCA With Multiple Components"
The official repository for "The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance". Code will be posted here upon publication.
scikit-learn compatible implementation of stability selection.
Code for NaiveFeatureSelection, i.e. feature selection in Naive Bayes, see https://arxiv.org/abs/1905.09884
Metric learning algorithms in Python
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.
An integer linear program solver using a Lagrange decomposition into binary decision diagrams. Lagrange multipliers are updated through dual block coordinate ascent.