research
∙
04/14/2021
Enabling Machine Learning Algorithms for Credit Scoring – Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models
Rapid development of advanced modelling techniques gives an opportunity ...
share
research
∙
09/28/2020
Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring
A major requirement for credit scoring models is to provide a maximally ...
research
∙
09/24/2020
Landscape of R packages for eXplainable Artificial Intelligence
The growing availability of data and computing power fuels the developme...
research
∙
06/02/2020
Interpretable Meta-Measure for Model Performance
Measures for evaluation of model performance play an important role in M...
research
∙
02/11/2020
Lifting Interpretability-Performance Trade-off via Automated Feature Engineering
Complex black-box predictive models may have high performance, but lack ...
research
∙
08/24/2019
EPP: interpretable score of model predictive power
The most important part of model selection and hyperparameter tuning is ...
research
∙
03/27/2019
iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models
Explainable Artificial Intelligence (XAI) brings a lot of attention rece...
research
∙
02/28/2019
SAFE ML: Surrogate Assisted Feature Extraction for Model Learning
Complex black-box predictive models may have high accuracy, but opacity ...
research
∙
09/19/2018
auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics
Machine learning models have spread to almost every area of life. They a...
research
∙
09/19/2018