SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 2431–2440 of 3304 papers

TitleStatusHype
MultiView Diffusion Maps—0
Multi-view Dimensionality Reduction for Dialect Identification of Arabic Broadcast Speech—0
Multi-View Kernels for Low-Dimensional Modeling of Seismic Events—0
Multi-view Locality Low-rank Embedding for Dimension Reduction—0
Multi-view Reconstructive Preserving Embedding for Dimension Reduction—0
Multiview Transformer: Rethinking Spatial Information in Hyperspectral Image Classification—0
NASARI: a Novel Approach to a Semantically-Aware Representation of Items—0
Natural data structure extracted from neighborhood-similarity graphs—0
Natural language processing for clusterization of genes according to their functions—0
Nature Inspired Dimensional Reduction Technique for Fast and Invariant Visual Feature Extraction—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified