2020, Data Collection, Knowledge Discovery and Modeling

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. 2020) propose the following foundational set of methods to classify various approaches for explaining deep ANNs.

Modeling

Modeling Deep Learning Machine Learning Knowledge Discovery

On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. Thanks to their might, now scientists and practitioners can develop innovative ways of collecting, storing, processing, and, ultimately, finding patterns in data.

Knowledge Discovery

Knowledge Discovery Experimentation Data-driven Metadata

Data Leaders Brief

Explaining black-box models using attribute importance, PDPs, and LIME

On the Hunt for Patterns: from Hippocrates to Supercomputers

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