SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2771–2780 of 3304 papers

TitleStatusHype
Pointed subspace approach to incomplete data—0
Offline Handwritten Recognition of Malayalam District Name - A Holistic Approach—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
Single-Pass PCA of Large High-Dimensional Data—0
Leveraging Patient Similarity and Time Series Data in Healthcare Predictive Models—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
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