SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1941–1950 of 3304 papers

TitleStatusHype
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization—0
Review of Swarm Intelligence-based Feature Selection Methods—0
Revisiting Classical Multiclass Linear Discriminant Analysis with a Novel Prototype-based Interpretable Solution—0
Rewards-based image analysis in microscopy—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
Riemannian Principal Component Analysis—0
Rigorous Restricted Isometry Property of Low-Dimensional Subspaces—0
RIPML: A Restricted Isometry Property based Approach to Multilabel Learning—0
Risk and optimal policies in bandit experiments—0
Risk factor aggregation and stress testing—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