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 3111–3120 of 3304 papers

TitleStatusHype
Linear Contour Learning: A Method for Supervised Dimension Reduction—0
Mixed-Variate Restricted Boltzmann Machines—0
A Flexible Iterative Framework for Consensus Clustering—0
Multilayer bootstrap networks—0
TCDSCSS: Dimensionality Reduction to Evaluate Texts of Varying Lengths - an IR Approach—0
Contrasting Syntagmatic and Paradigmatic Relations: Insights from Distributional Semantic Models—0
Distributional Semantics in R with the wordspace Package—0
Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor—0
Hyperspectral Imaging and Analysis for Sparse Reconstruction and Recognition—0
Enhancing the Accuracy of Biometric Feature Extraction Fusion Using Gabor Filter and Mahalanobis Distance Algorithm—0
Show:102550
← PrevPage 312 of 331Next →
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