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 1561–1570 of 3304 papers

TitleStatusHype
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality—0
A Clustering Framework for Residential Electric Demand ProfilesCode0
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data—0
Brain Inspired Face Recognition: A Computational Framework—0
A hyperparameter-tuning approach to automated inverse planningCode1
Forensic Analysis of Video Files Using Metadata—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction—0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection ApproachCode0
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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