Feng et al., 2023 - Google Patents
One-dimensional VGGNet for high-dimensional dataFeng et al., 2023
- Document ID
- 5937429513178852187
- Author
- Feng S
- Zhao L
- Shi H
- Wang M
- Shen S
- Wang W
- Publication year
- Publication venue
- Applied Soft Computing
External Links
Snippet
We consider a deep learning model for classifying high-dimensional data and seek to achieve optimal evaluation accuracy and robustness based on multicriteria decision-making (MCDM) for high-dimensional data analysis applications during comprehensive evaluation …
- 238000011156 evaluation 0 abstract description 45
Classifications
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- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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