Interpretability in deep learning for finance: A case study for the Heston model

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

A total of 737 treatment-naïve patients with CLL diagnosed at Mayo Clinic were included in this study. We compared predictive abilities for two survival models (Cox proportional hazards and random ...
mccormick.northwestern.edu

Exploring the Connections Among Machine Learning, Interpretability, and Logic

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...
InfoQ

Understanding and Debugging Deep Learning Models: Exploring AI Interpretability Methods

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Microsoft

Microsoft responsible machine learning capabilities build trust in AI systems, developers say

Anyone who runs a business knows that one of the hardest things to do is accuse a customer of malfeasance. That’s why, before members of Scandinavian Airlines’ (SAS) fraud detection unit accuse a ...
Scientific Research Publishing

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ()

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
ascopubs.org

Improved Interpretability of Machine Learning Model Using Unsupervised Clustering: Predicting Time to First Treatment in Chronic Lymphocytic Leukemia

PROSPeCT: A Predictive Research Online System for Prostate Cancer Tasks Time to event is an important aspect of clinical decision making. This is particularly true when diseases have highly ...