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 2141–2150 of 3304 papers

TitleStatusHype
Stochastic Multidimensional Scaling—0
Stochastic Neighbor Embedding—0
Stochastic Neighbor Embedding separates well-separated clusters—0
Stochastic variance reduced multiplicative update for nonnegative matrix factorization—0
Stock Price Prediction using Principle Components—0
Strategy for Rapid Diabetic Retinopathy Exposure Based on Enhanced Feature Extraction Processing—0
Stratospheric aerosol source inversion: Noise, variability, and uncertainty quantification—0
Strong and weak principles of neural dimension reduction—0
Structural Learning and Integrative Decomposition of Multi-View Data—0
Structured adaptive and random spinners for fast machine learning computations—0
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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