Constructing Explainable Classifiers from the Start—Enabling Human-in-the Loop Machine Learning

Constructing Explainable Classifiers from the Start—Enabling Human-in-the Loop Machine Learning

Interactive machine learning (IML) enables the incorporation of human expertise because the human participates in the construction of the learned model. Moreover, with human-in-the-loop machine learning (HITL-ML), the human experts drive the learning, and they can steer the learning objective not on...

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Bibliographic Details
Main Authors: Vladimir Estivill-Castro, Eugene Gilmore, René Hexel
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Information
Subjects:
interactive machine learning
decision tree classifiers
transparent-by-design
parallel coordinates
Online Access:https://www.mdpi.com/2078-2489/13/10/464

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