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 281–290 of 3304 papers

TitleStatusHype
A Multimodal Data-driven Framework for Anxiety Screening—0
A Multi-Fidelity Methodology for Reduced Order Models with High-Dimensional Inputs—0
A Deep Graph Embedding Network Model for Face Recognition—0
Grading and Anomaly Detection for Automated Retinal Image Analysis using Deep Learning—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Achieving Fair PCA Using Joint Eigenvalue Decomposition—0
3-Dimensional residual neural architecture search for ultrasonic defect detection—0
Application of Deep Learning for Predictive Maintenance of Oilfield Equipment—0
Application of Dimensional Reduction in Artificial Neural Networks to Improve Emergency Department Triage During Chemical Mass Casualty Incidents—0
Applying Graph-based Keyword Extraction to Document Retrieval—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