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 2061–2070 of 3304 papers

TitleStatusHype
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making PathsCode0
Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point-wise Anomaly Detection—0
ShapeVis: High-dimensional Data Visualization at Scale—0
Supervised Discriminative Sparse PCA with Adaptive Neighbors for Dimensionality ReductionCode0
A Correspondence Analysis Framework for Author-Conference Recommendations—0
A kernel Principal Component Analysis (kPCA) digest with a new backward mapping (pre-image reconstruction) strategy—0
Review of Single-cell RNA-seq Data Clustering for Cell Type Identification and Characterization—0
MODiR: Multi-Objective Dimensionality Reduction for Joint Data Visualisation—0
Upper bounds for Model-Free Row-Sparse Principal Component Analysis—0
Estimating Model Uncertainty of Neural Network in Sparse Information Form—0
Show:102550
← PrevPage 207 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