SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2781–2790 of 3304 papers

TitleStatusHype
Pointed subspace approach to incomplete data—0
Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors—0
Expressing Facial Structure and Appearance Information in Frequency Domain for Face Recognition—0
Locality Preserving Projections for Grassmann manifold—0
Leveraging Patient Similarity and Time Series Data in Healthcare Predictive Models—0
Single-Pass PCA of Large High-Dimensional Data—0
Adaptive Neighboring Selection Algorithm Based on Curvature Prediction in Manifold Learning—0
Joint Semi-supervised RSS Dimensionality Reduction and Fingerprint Based Algorithm for Indoor Localization—0
Enhancing Robustness of Machine Learning Systems via Data Transformations—0
MLC Toolbox: A MATLAB/OCTAVE Library for Multi-Label 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