Variable Importance Using Target Shuffling

This is the recording of Dean Abbott's talk at KNIME Summit 2016 with title "

John Elder President & Founder of Elder Research introduces his upcoming talk on

In this short video, Max Margenot gives an overview of selecting features for your model. He goes over the process of adding ...

Computer Science/Discrete Mathematics Seminar I 11:00am|West Lecture Hall and Remote Access Topic:

A song explaining machine learning interpretability methods, focusing on three techniques for measuring feature

"The Fisher–Yates

SHAP is the most powerful Python package for understanding and debugging your machine-learning models. We learn to ...

To train machine learning models we need to provide the model

In order to explain what a black box algorithm does, we can start by studying which

Video abstract for the Strategic Management Journal article, "Making the most of AI and machine learning in organizations and ...

Target Variable Selection

SVM can only produce linear boundaries between classes by default, which not enough for most machine learning applications.

Explainable AI techniques beyond SHAP include Integrated Gradients (IG) and counterfactual explanations, which help interpret ...

Have you ever wondered whether your machine learning model is a chance prediction? In this video, I will show you how to prove ...