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cs.LG2024
Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension
Shuang Ni, Adrien Aumon, Guy Wolf +2
The value of supervised dimensionality reduction lies in its ability to uncover meaningful connections between data features and labels. Common dimensionality reduction methods emb…
cs.LG2024
Noisy Data Visualization using Functional Data Analysis
Haozhe Chen, Andres Felipe Duque Correa, Guy Wolf +1
Data visualization via dimensionality reduction is an important tool in exploratory data analysis. However, when the data are noisy, many existing methods fail to capture the under…