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 2801–2810 of 3304 papers

TitleStatusHype
Auto-adaptative Laplacian Pyramids for High-dimensional Data Analysis—0
Auto-Detection of Safety Issues in Baby Products—0
Autoencoder Enhanced Realised GARCH on Volatility Forecasting—0
Auto-encoding brain networks with applications to analyzing large-scale brain imaging datasets—0
Autoencoding topology—0
Autoencoding with a Learning Classifier System: Initial Results—0
Automated Anomaly Detection on European XFEL Klystrons—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Automated Disease Normalization with Low Rank Approximations—0
Automatic Collection Creation and Recommendation—0
Show:102550
← PrevPage 281 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