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 3221–3230 of 3304 papers

TitleStatusHype
Distributional Semantics in R with the wordspace Package—0
Distribution-based Label Space Transformation for Multi-label Learning—0
Diverse Landmark Sampling from Determinantal Point Processes for Scalable Manifold Learning—0
DNA Methylation Data to Predict Suicidal and Non-Suicidal Deaths: A Machine Learning Approach—0
Supporting Safety Analysis of Image-processing DNNs through Clustering-based Approaches—0
Does a Hybrid Neural Network based Feature Selection Model Improve Text Classification?—0
Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning—0
Domain-Dependent Speaker Diarization for the Third DIHARD Challenge—0
Domain Generalization via Domain-based Covariance Minimization—0
Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors—0
Show:102550
← PrevPage 323 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