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 1661–1670 of 3304 papers

TitleStatusHype
Forensic Analysis of Video Files Using Metadata—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction—0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection ApproachCode0
Contextual Bandits with Sparse Data in Web setting—0
Ovarian Cancer Detection based on Dimensionality Reduction Techniques and Genetic Algorithm—0
Automatic Collection Creation and Recommendation—0
Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombinationCode0
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction NetworksCode0
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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