Constructing and Visualizing High-Quality Classifier Decision Boundary Maps

Constructing and Visualizing High-Quality Classifier Decision Boundary Maps

Visualizing decision boundaries of machine learning classifiers can help in classifier design, testing and fine-tuning. Decision maps are visualization techniques that overcome the key sparsity-related limitation of scatterplots for this task. To increase the trustworthiness of decision map use, we...

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Bibliographic Details
Main Authors: Francisco C. M. Rodrigues, Mateus Espadoto, Roberto Hirata, Alexandru C. Telea
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Information
Subjects:
machine learning
dimensionality reduction
image-based visualization
Online Access:https://www.mdpi.com/2078-2489/10/9/280

Internet

https://www.mdpi.com/2078-2489/10/9/280

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