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 2721–2730 of 3304 papers

TitleStatusHype
Application of Deep Learning for Predictive Maintenance of Oilfield Equipment—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
Application of Dimensional Reduction in Artificial Neural Networks to Improve Emergency Department Triage During Chemical Mass Casualty Incidents—0
Application of Fuzzy Clustering for Text Data Dimensionality Reduction—0
Application of Symmetric Uncertainty and Mutual Information to Dimensionality Reduction and Classification of Hyperspectral Images—0
Application Research On Real-Time Perception Of Device Performance Status—0
Applications of machine learning to predict seasonal precipitation for East Africa—0
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics—0
Applying a random projection algorithm to optimize machine learning model for predicting peritoneal metastasis in gastric cancer patients using CT images—0
Applying a random projection algorithm to optimize machine learning model for breast lesion classification—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