SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 991–1000 of 3304 papers

TitleStatusHype
Fast conformational clustering of extensive molecular dynamics simulation dataCode1
Fair Recommendation by Geometric Interpretation and Analysis of Matrix Factorization—0
Latent Autoregressive Source SeparationCode1
Topologically Regularized Data EmbeddingsCode0
Principal Component Analysis in Space FormsCode1
EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulationCode0
Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis—0
KIDS: kinematics-based (in)activity detection and segmentation in a sleep case study—0
ClusTop: An unsupervised and integrated text clustering and topic extraction framework—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and Dimensionality Reduction—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