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 2331–2340 of 3304 papers

TitleStatusHype
Noisy multi-label semi-supervised dimensionality reduction—0
Exploring Language Similarities with Dimensionality Reduction TechniqueCode0
Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank—0
Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"—0
Distance metric learning based on structural neighborhoods for dimensionality reduction and classification performance improvement—0
Can Genetic Programming Do Manifold Learning Too?—0
Show:102550
← PrevPage 234 of 331Next →
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