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An Empirical Evaluation of the t-SNE Algorithm for Data Visualization in Structural Engineering
[article]
2021
arXiv
pre-print
A fundamental task in machine learning involves visualizing high-dimensional data sets that arise in high-impact application domains. When considering the context of large imbalanced data, this problem becomes much more challenging. In this paper, the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm is used to reduce the dimensions of an earthquake engineering related data set for visualization purposes. Since imbalanced data sets greatly affect the accuracy of classifiers, we
arXiv:2109.08795v1
fatcat:d6ave5xj2zbdhclg2rftdjvdqy