From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
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KNIME's Local Explanation View node - KNIME Tutorial
From the course: Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
KNIME's Local Explanation View node
- [Instructor] The team at Knime really tries to make it easy to learn new features. In almost every instance when a new feature comes out, you can count on eventually having a blog post, a practice workflow, and discussion. So you can see here that they have a feature called the Local Explanation View. I've downloaded the relevant workflow and you can too simply by going to the Knime hub and either finding the workflow or the blog post, everything is cross-referenced. Here we are in Knime, and here's the workflow, it's called, this is their numbering now: XAI Credit Scoring Example Local Explanations View. And we can make this a little bit bigger by looking only at that screen. And then let's see if we can fit 125%, which we can. So we're bringing in the credit scoring data. I just want to point out one particular issue of this workflow before we look at the local explanation view. And that is that there's a row sampling…
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Contents
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Developing an intuition for Shapley values4m 35s
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Introducing SHAP1m 48s
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Using LIME to provide local explanations for neural networks2m 23s
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What are counterfactuals?2m 27s
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KNIME's Local Explanation View node4m 3s
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XAI View node demonstrating KNIME6m 41s
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