SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 531–540 of 3304 papers

TitleStatusHype
Application of Symmetric Uncertainty and Mutual Information to Dimensionality Reduction and Classification of Hyperspectral Images—0
Application of Fuzzy Clustering for Text Data Dimensionality Reduction—0
A Harmonic Mean Linear Discriminant Analysis for Robust Image Classification—0
Application of Dimensional Reduction in Artificial Neural Networks to Improve Emergency Department Triage During Chemical Mass Casualty Incidents—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
A Hardware-Friendly Algorithm for Scalable Training and Deployment of Dimensionality Reduction Models on FPGA—0
A Critical Note on the Evaluation of Clustering Algorithms—0
Chiron: A Robust Recommendation System with Graph Regularizer—0
Application of Deep Learning for Predictive Maintenance of Oilfield Equipment—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—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