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 1821–1830 of 3304 papers

TitleStatusHype
Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data—0
Privacy-Preserving Machine Learning Using EtC Images—0
PRKAN: Parameter-Reduced Kolmogorov-Arnold Networks—0
Probabilistic Bearing Fault Diagnosis Using Gaussian Process with Tailored Feature Extraction—0
Probabilistic Dimensionality Reduction via Structure Learning—0
Probabilistic low-rank matrix completion on finite alphabets—0
Probabilistic partition of unity networks for high-dimensional regression problems—0
Probabilistic Principal Geodesic Analysis—0
Probabilistic Relational PCA—0
Probability distributions for analog-to-target distances—0
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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