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 1301–1310 of 3304 papers

TitleStatusHype
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
A Hybrid Approach for Binary Classification of Imbalanced Data—0
Active Learning with TensorBoard Projector—0
Covariance matrix preparation for quantum principal component analysis—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Applying Ricci Flow to High Dimensional Manifold Learning—0
Coupling the reduced-order model and the generative model for an importance sampling estimator—0
Applying Graph-based Keyword Extraction to Document Retrieval—0
A hierarchical approach with feature selection for emotion recognition from speech—0
Coupled Control Systems: Periodic Orbit Generation with Application to Quadrupedal Locomotion—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