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Article Jorge Jaramillo Herrera · 17 hr ago 19m read

Explainability in ML Models

This article introduces SHAP explainability methods as an approach to understand the reasons behind predictions in machine learning black-box models. It also includes a simple Jupyter notebook that you can use and modify to gain hands-on experience with these concepts:

https://www.kaggle.com/code/jorgeivnjh/explainability-in-ml-models

https://github.com/JorgeIvanJH/Explainability-in-ML-models

We will leverage these concepts for a future implementation in our Continuous Training Pipeline: https://community.intersystems.com/post/complementing-iris-mlflow-continuous-training-ct-pipeline

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Question Kenji Kishimoto · Apr 29

IRIS Management Portal lag and terminal input latency when running background automation tasks

Hi everyone,

I’ve been diving into the new IRIS 2026.1 features this week, specifically trying out the opt-in modernized Interoperability UI and the new DTL Explainer, but I’ve recently hit a persistent technical snag where the Management Portal becomes incredibly sluggish and my Terminal sessions start to experience significant input latency.

I am currently using a community setup to handle some automated local logging and script-based data scrubbing for my production archives in the background while I work.

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