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Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction
[article]
2021
arXiv
pre-print
Modern data analytics take advantage of ensemble learning and transfer learning approaches to tackle some of the most relevant issues in data analysis, such as lack of labeled data to use to train the analysis models, sparsity of the information, and unbalanced distributions of the records. Nonetheless, when applied to multimodal datasets (i.e., datasets acquired by means of multiple sensing techniques or strategies), the state-of-theart methods for ensemble learning and transfer learning might
arXiv:2105.03682v1
fatcat:jznrxvrir5hs5bq4qxhzvmzpi4