SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 801–810 of 3304 papers

TitleStatusHype
An Incremental Dimensionality Reduction Method for Visualizing Streaming Multidimensional Data—0
A Bilinear Programming Approach for Multiagent Planning—0
A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms—0
Dimensionality Reduction via Diffusion Map Improved with Supervised Linear Projection—0
A Light weight and Hybrid Deep Learning Model based Online Signature Verification—0
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification—0
Deep Manifold Computing and Visualization Using Elastic Locally Isometric Smoothness—0
Deep Manifold Transformation for Nonlinear Dimensionality Reduction—0
Deep matrix factorizations—0
Detection of Alzheimer's Disease Using Graph-Regularized Convolutional Neural Network Based on Structural Similarity Learning of Brain Magnetic Resonance Images—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