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 71–80 of 3304 papers

TitleStatusHype
Unsupervised outlier detection to improve bird audio dataset labels—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—0
Learning Isometric Embeddings of Road Networks using Multidimensional Scaling—0
Interpretable non-linear dimensionality reduction using gaussian weighted linear transformationCode0
Online model learning with data-assimilated reservoir computers—0
I-Con: A Unifying Framework for Representation Learning—0
MPAD: A New Dimension-Reduction Method for Preserving Nearest Neighbors in High-Dimensional Vector Search—0
A Graph Based Raman Spectral Processing Technique for Exosome Classification—0
Impact of Latent Space Dimension on IoT Botnet Detection Performance: VAE-Encoder Versus ViT-Encoder—0
Word Embedding Techniques for Classification of Star Ratings—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