Interpretable Machine Learning for SME Financial Distress Prediction
- 5 February 2023
- book chapter
- Published by Springer Nature
- p. 454-464
Abstract
No abstract availableKeywords
This publication has 21 references indexed in Scilit:
- Statistical and machine learning models in credit scoring: A systematic literature surveyApplied Soft Computing, 2020
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AIInformation Fusion, 2020
- Explainability of a Machine Learning Granting Scoring Model in Peer-to-Peer LendingIEEE Access, 2020
- From local explanations to global understanding with explainable AI for treesNature Machine Intelligence, 2020
- A robust multi-batch L-BFGS method for machine learningOptimization Methods and Software, 2019
- Credit Risk Analysis Using Machine and Deep Learning ModelsSSRN Electronic Journal, 2018
- ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R2017
- XGBoost2016
- "Why Should I Trust You?"2016
- A more complete conceptual framework for SME financeJournal of Banking & Finance, 2006