JOSS Papers: explainability

All Papers
4113
 Published Papers
3747
 Active Papers
366
published Published 5 months ago

WoodTapper: a Python package for explaining decision tree ensembles

Python Jupyter Notebook Julia R
@Abdoulaye-SAKHO
10.21105/joss.10112
published Published about 1 year ago

Explabox: A Python Toolkit for Standardized Auditing and Explanation of Text Models

Python
@marcelrobeer
10.21105/joss.08253
published Published over 1 year ago

AI-ANNE: (A) (N)eural (N)et for (E)xploration

Python Jupyter Notebook
@statistical-thinking
10.21105/joss.08039
published Published almost 3 years ago

Scarlet: Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic

Python
@ritamraha
10.21105/joss.05052
published Published almost 3 years ago

pudu: A Python library for agnostic feature selection and explainability of Machine Learning spectroscopic problems

Python
@enricgrau
10.21105/joss.05873
published Published almost 4 years ago

DIANNA: Deep Insight And Neural Network Analysis

Python Jupyter Notebook
@elboyran
10.21105/joss.04493
published Published almost 4 years ago

GSAreport: Easy to Use Global Sensitivity Reporting

Python Jupyter Notebook
@Basvanstein
10.21105/joss.04721
published Published almost 5 years ago

TX$^2$: Transformer eXplainability and eXploration

Python
@WarmCyan
10.21105/joss.03652
published Published over 5 years ago

imodels: a python package for fitting interpretable models

Python Jupyter Notebook
@csinva
10.21105/joss.03192
published Published over 6 years ago

shapr: An R-package for explaining machine learning models with dependence-aware Shapley values

R Python C++
@martinju
10.21105/joss.02027
Displaying papers 1 - 10 of 14 in total

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ISSN 2475-9066