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MultiCaM-Vis: Visual Exploration of Multi-Classification Model with High Number of Classes by Dilawer, Syed Ahsan Ali; Humayoun, Shah Rukh is a scholarly article available to read on EtoBox.

What is MultiCaM-Vis: Visual Exploration of Multi-Classification Model with High Number of Classes about?

Visual exploration of multi-classification models with large number of classes would help machine learning experts in identifying the root cause of a problem that occurs during learning phase such as miss-classification of instances. Most of the previous visual analytics solutions targeted only a few classes. In this paper, we present our interactive visual analytics tool, called MultiCaM-Vis, that provides \Emph{overview+detail} style parallel coordinate views and a Chord diagram for exploration and inspection of class-level miss-classification of instances. We also present results of a preliminary user study with 12 participants.

Author

Dilawer, Syed Ahsan Ali; Humayoun, Shah Rukh

Published

2023

Language

EN