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 2671–2680 of 3304 papers

TitleStatusHype
A new method color MS-BSIF Features learning for the robust kinship verification—0
A New Method for Performance Analysis in Nonlinear Dimensionality Reduction—0
A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data—0
A new set of cluster driven composite development indicators—0
A New Spatio-Spectral Morphological Segmentation For Multi-Spectral Remote-Sensing Images—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—0
Angle constrained path to cluster multiple manifolds—0
Angular Embedding: A New Angular Robust Principal Component Analysis—0
An Image-Based Fluid Surface Pattern Model—0
An Impossibility Theorem for Node Embedding—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