published Published over 2 years ago
pudu: A Python library for agnostic feature selection and explainability of Machine Learning spectroscopic problems
Python
@enricgrau
published Published over 2 years ago
SIRUS.jl: Interpretable Machine Learning via Rule Extraction
Julia
@rikhuijzer
published Published about 3 years ago
TSInterpret: A Python Package for the Interpretability of Time Series Classification
Python
@JHoelli
@markheckmann
published Published almost 5 years ago
starry_process: Interpretable Gaussian processes for stellar light curves
Python C++ C
@rodluger
published Published about 5 years ago
imodels: a python package for fitting interpretable models
Python Jupyter Notebook
@csinva
published Published over 6 years ago
shapr: An R-package for explaining machine learning models with dependence-aware Shapley values
R Python C++
@martinju
@pssachdeva
published Published over 6 years ago
modelStudio: Interactive Studio with Explanations for ML Predictive Models
R JavaScript
@hbaniecki
published Published almost 7 years ago
@matiszak
