SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1171–1180 of 3304 papers

TitleStatusHype
Deep Manifold Transformation for Nonlinear Dimensionality Reduction—0
Deep Manifold Computing and Visualization Using Elastic Locally Isometric Smoothness—0
Asteroids co-orbital motion classification based on Machine Learning—0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Deep Linear Discriminant Analysis with Variation for Polycystic Ovary Syndrome Classification—0
A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms—0
A Light weight and Hybrid Deep Learning Model based Online Signature Verification—0
Deep Learning Multidimensional Projections—0
A Stable Measure for Conditional Periodicity of Time Series using Persistent Homology—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